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To Win in the AI Economy, You Need More Than a Strategy, You Need a Mindshift

Earlier this year, I was asked to deliver the opening keynote at Avasant’s Empowering Beyond Summit. The event was attended by some of the most influential leaders in business and technology. I learned from each of them their challenges and opportunities with AI and wanted to share my takeaways here. Also, the team uploaded the presentation to Youtube and I’ve included it below!

When people talk about AI, they often default to automation. It’s the low-hanging fruit…faster execution, lower costs, streamlined operations. But automation is only one side of the AI coin. The other side, the more powerful, game-changing side, is augmentation. But for some reason, we don’t really want to talk about it. Why? Maybe because at its core, we’re really talking about innovation and transformation. And even though it’s reimagination, change is hard…and expensive. But ignoring it doesn’t in any way ensure survival. So, we ignore it at our own peril.

Start with a mindshift.

At Avasant’s Empowering Beyond Summit in Huntington Beach, I spoke to a room of global technology and business leaders about what AI really represents. Spoiler: it’s not digital transformation. That era, defined largely by digitizing legacy processes, is over. This is business transformation. And AI is not just the next tool in the box. It’s the beginning of a new box entirely.

We’re Not Thinking Big Enough

Let’s be honest. The appetite for transformation isn’t widespread. Most executives don’t want to invent the future, they just want to improve yesterday for tomorrow while taking out costs and driving efficiency. The problem? That’s not transformation. That’s iteration. And iteration eventually loses its capacity to defend against digital Darwinism.

If we keep using AI to do the same things slightly better, faster, or cheaper, we’ll get efficiency. But we won’t get reinvention. The real value of AI doesn’t lie in what it can do for our current operations. It lies in what it enables us to do that we never could before.

Leaders are already promising the street that AI will deliver performance gains. Yet behind closed doors, many admit they’re ambivalent or dissatisfied with the ROI. Why? Because we’re still coloring inside the lines of the old business model. AI deserves…and demands…an entirely new canvas.

The Iteration-Innovation Gap

Most companies today are investing in what I call optimized AI, deploying tools to supercharge legacy workflows. And that’s fine. But it’s not a revolution. Innovative AI, on the other hand, explores use cases that never existed, redesigns workflows for exponential outcomes, and asks questions like “What would AI do?” instead of “How can AI help me do what I’ve always done?”

Too many executives are still playing it safe, waiting for use cases to become obvious. But transformation doesn’t come with a prewritten playbook. If you wait until there’s a roadmap, you’re already behind.

The Risk Isn’t AI. The Risk Is Inaction.

Venture capitalists understand this intuitively. When they back a startup, they’re not looking for a 10x return. They’re looking for 1000x…moonshot ideas that redefine industries. Founders don’t show up with risk-averse ideas or fully validated business models. They lead with vision.

Why should enterprise leaders be any different?

We need to borrow that VC mindset and apply it to how we invest in AI. That means creating space for innovation, rewarding calculated risk, and enabling teams to operate outside the boundaries of business as usual. It also means acknowledging that the biggest barrier to scale isn’t talent. It’s us…the leaders, decision-makers, shareholders and stakeholders, and boards.

Automation vs. Augmentation: The IKEA Lesson

One of my favorite recent examples of augmentation comes from IKEA. They deployed an AI chatbot, “Billy,” which handled 57% of customer service inquiries. But instead of laying off staff, IKEA reimagined the remaining 43% of calls, many of which were about interior design, and reskilled those employees as design consultants. The result? A brand-new service and €1 billion in new revenue in one year.

That’s what augmentation looks like: not just doing the same work with fewer people, but using AI to create entirely new value. That’s the kind of thinking every leader needs to adopt.

Mind the (Leadership) Gap

Recent studies show that executives overwhelmingly believe their companies are ahead in AI adoption. Their employees, however, aren’t on the same page. Whether it’s AI strategy, literacy, or execution, the perception gap is real, and dangerous.

You can’t lead people into the future if they don’t understand the mission. AI transformation requires culture change, new mental models, and above all, psychological safety. Google’s own research shows that high-performing teams are not the ones with the best credentials. The HiPo teams feel safe to experiment, challenge conventions, and ask bold questions.

It’s Time to Rewrite the Org Chart

Yes, AI will be on your org chart. But the more important question is: where? And how will it collaborate with your people? Augmented intelligence isn’t about replacing humans; it’s about unlocking capacity, creativity, and entirely new performance metrics.

We need to redesign job descriptions so they reflect AI-human collaboration. We need to reward people not just for doing their jobs more efficiently, but for doing things AI enables them to do that were previously impossible.

This is how we move from automation to transformation. This is how we build infinitely scalable organizations.

The Road Ahead: Business Acceleration Over Digital Transformation

Forget digital transformation. It’s time for business acceleration. For platform thinking. For bold investments in innovative AI alongside the iterative.

The question is more than “How can we use AI to automate and save costs?” It’s:

What new capabilities can we unlock?

What new business models can we design?

In which ways can AI help us create new value?

What would our company look like if we started today with AI at the core?

You are the Leader Behind the Leader

Let’s face it: most boards and C-suites still don’t know what they don’t know. That’s where you come in.

You are the visionary who helps them see what’s possible. You are the catalyst who shifts the conversation from “What can we automate?” to “What can we create?” You are the leader behind the leader.

In the end, a great leader doesn’t just adapt to the future. They invent it. And if we do this right, AI is both a tool to survive. And it’s a partner we collaborate with to innovate and thrive!

Are you ready for a Mindshift ?

Book Brian to speak at your event! 

The post To Win in the AI Economy, You Need More Than a Strategy, You Need a Mindshift appeared first on Brian Solis.

Beyond the Hype: The Real State of AI in Business

Let me ask you a question…

What’s moving faster, AI innovation or the rate at which organizations fall behind?

While AI continues to advance at breakneck speed, many legacy companies are struggling to keep pace. The real challenge isn’t the technology itself, but the growing gap in alignment and execution. Most CEOs and board members believe they’re confidently leading their organizations into the AI era. Yet new data reveals a stark disconnect between the C-suite and frontline employees when it comes to what’s actually happening on the ground.

According to an Axios survey that interviewed CEOs and their employees, separately, AI vision, strategy, and capacity may be a dangerous illusion.

Axios learned that CEOs may feel they are steering their companies into an AI-powered future. But if the people responsible for delivering on that vision don’t feel informed, empowered, or included, then the transformation will fail to take root. Sound familiar?

Let’s talk about it!

C-Suites are mistaking AI vision with tactical strategy. And they’re mistaking AI strategy for strategy activation. Employees don’t feel the impact, which means vision isn’t articulated and strategy isn’t embedded.

The Illusion of Vision and Strategy

Nearly 90 of C-Suites say their company has an AI strategy. Yet only 57% of employees believe that to be true.

This suggests that while the strategy might exist in executive slide decks or boardroom conversations, it hasn’t been translated into the day-to-day reality for most employees. For them, the strategy is either invisible or irrelevant. Again, sound familiar?

The Illusion of Success

Executives also believe they’ve made meaningful progress. Seventy-five percent say the company has been successful in adopting AI over the past 12 months. But just 45% of employees agree. If employees aren’t feeling the impact of success, that means the change isn’t penetrating deeply enough. If those delivering the work don’t feel the benefits, innovation won’t scale.

The Illusion of Control

Another significant divide emerges when asked whether the company’s approach to AI is “well-controlled and highly strategic.” While 73% of C-suite leaders say yes, only 47% of employees agree. That’s a 26-point gap in perception and reality!

A strategy is only as effective as it is understood and executed across the organization. If people perceive confusion or chaos where leadership sees control, well, you can imagine what happens next.

From Illusion to Introspection

If the first set of data reveals a disconnect between leadership and the workforce, the second reveals something even more revealing. Here, we shift to a profound introspection among CEOs themselves. They reveal more than disconnects in communication. They’re disconnects of modern leadership.

The illusion of progress is being shattered by the very leaders tasked with shaping the future. CEOs are quietly confessing that AI is transforming how businesses operate. And it’s redefining who leads, how decisions are made, and what it takes to stay relevant.

Let’s compare these findings to the Dataiku/Harris, “Global AI Confessions Report: CEO Edition.” This survey of 500 CEOs worldwide unveils startling admissions and revelations of Al’s impact on corporate leadership and competitive survival.

94% of CEOs admit an Al agent could provide equal or better counsel on business decisions than a human board member.

What it means (WIM):

The boardroom is no longer immune to disruption. AI literacy is now a fiduciary responsibility. Boards must evolve from oversight to insight, becoming fluent in AI, risk, and opportunity at the same pace as the technology itself.

What to do (WTD):

Establish an AI Board Advisor Program to embed AI-powered agents and advisors alongside traditional governance models.

Test AI-simulated board scenarios to understand what it sees that your board doesn’t.

89 of CEOs feel AI can develop an equal or better strategic plan than a member of their own exec team.

WIM:

Strategic planning is no longer a purely human exercise. The executive bench must now compete and collaborate with algorithmic intelligence and do so quickly and visibly. The future leadership team will be hybrid: human + digital counterparts.

WTD:

Augment strategic planning with AI agents that simulate market changes, competitor responses, and future scenarios (agents as digital twins FTW!)

Redesign the org chart with AI-native roles. Train your teams to collaborate with AI not just as tools, but as cognitive partners.

74% of CEOs admit they’ll lose their job within 2 years if they don’t deliver Al business gains.

WIM:

The AI clock is ticking, and the innovation imperative is rising. AI native companies are moving the game from an era of AI experimentation to execution. AI-forward boards and shareholders will learn to see AI beyond a tool or technology investment, and instead as a performance expectation and competitive driver.

WTD:

CEOs must shift from exploring peer-driven AI use cases to engineering AI-native business models. Leaders must stop waiting and start leading.

Create an AI Transformation Office to orchestrate enterprise-wide AI initiatives, beyond the AI ‘status quo’ pilots.

Tie AI metrics to business outcomes including, revenue growth, margin expansion, NPS, time to market. Develop a real AI vision!

Publish a 12-month AI innovation roadmap to the board, employees, and investors. Then, deliver and report against it.

68% of CEOs claim they are involved in more than half of their companies’ Al-related decisions.

WIM:

CEOs understand, or are starting to, grasp the stakes and are stepping in and stepping up. But involvement doesn’t equal empowerment. AI readiness, AI fluency, and AI empowerment must be democratized across the enterprise, as tied to the vision.

WTD:

Build AI leadership coalitions or cross-functional stakeholder groups across functions, influencing but not limited to IT, to scale decision-making.

Bring in the outsiders to develop and execute an AI upskilling initiative across all management tiers.And perhaps the least intuitive of the bunch, distribute decision-making authority to AI-augmented teams trained to act with speed and insight.

From Reckoning to Renaissance

This is a reckoning and the beginning of something bigger. It’s AI transformation tied to leadership transformation.

The AI era demands a new leadership mindset. A new vision for what’s possible. A new language. A new social contract between leaders and their organizations.

That starts by closing the gap between perception and reality. It means rethinking leadership. It means moving beyond platitudes. You can’t scale what your teams don’t understand. And you can’t scale what you do not understand.This moment demands a bold new vision and a clear strategy. It demands action and empowerment across the organization.  It also demands measurable alignment between boardroom intent, C-Level promises, and frontline execution.

Without vision and alignment, AI remains theater. Without shared understanding, transformation stalls. And without communication and enablement, trust fails to materialize. The companies that succeed unite AI and business leadership, innovation, and culture.

The renaissance starts with a mindshift.

The post Beyond the Hype: The Real State of AI in Business appeared first on Brian Solis.

What Happens to Companies That Don’t Think Big Enough with AI?

I had the privilege of joining GoTo CMO Peter Mahoney on the Practically Tomorrow podcast. We talked about one of the most urgent, and misunderstood, topics of our time: how AI is reshaping the world of work. But this wasn’t just another conversation about automation and productivity. It was a much deeper exploration of how we need to rethink leadership, empathy, and innovation in the age of intelligent machines.

“The most dangerous thing for any organization of any size is when we do not think big enough with what we can do with AI.”

Why AI Requires More Than Automation

It’s tempting for companies to treat AI as a faster horse, another tool to speed up existing processes or reduce costs. But that’s not transformation. That’s stagnation, accelerated.

True transformation begins when we ask: What can we do now that was never possible before?

That’s why I draw a distinction between practical AI and innovative AI as inspired by GoTo’s research, “The Pulse of Work in 2025.”

Practical AI improves efficiency, reduces routine, and scales productivity.

Innovative AI creates new products, services, experiences, and even entirely new business models.

Most companies start with the practical. The most courageous and visionary leaders learn to balance both.

“AI isn’t here just to optimize yesterday’s work. It’s here to open up new frontiers of value creation.”

Curiosity Is the New Superpower

AI is a blank canvas. But many leaders are painting with old brushes. In the podcast, we explored how many employees, and even executives, aren’t getting the most out of AI because they’re using it like search engines. They’re prompting from yesterday’s mindset.

“You can’t imagine a better future if you’re looking at it through the same lens that created the past.”

If there’s one practical takeaway I’d offer any business leader, it’s this:

“Be curious. Lean into what you don’t know you don’t know. Ask what you can now do with AI that you couldn’t before.”

This curiosity unlocks a new mindset—one that helps you build not just a more efficient organization, but a more adaptive, inspired one.

Empathy Is Your Competitive Advantage

One of the most surprising and overlooked side effects of our accelerated digital lives is what I call digital narcissism. It’s not just a buzzword. It’s a behavioral shift where people have become the center of their own digital ecosystems, with heightened expectations and lower patience.

That makes empathy the most powerful (and underutilized) tool in your leadership toolbox.

“Empathy is experience. And experience is a feeling. There are only two kinds of experiences people remember…those that are amazing and those that suck.”

In the episode, I shared stories from working with retail leaders who had to walk through their own customer experiences to truly feel what their customers go through. When we embrace empathy, by observing, experiencing, and listening, we design better services, more engaging experiences, and ultimately, more resilient businesses.

AI Is a Mirror, ButWhat Will It Reflect?

One of the most important insights I’ve taken from years of studying technological shifts is this:

“AI will not just change how we work, it will reveal who we are.”

Some companies are already operating like 24/7 organizations where AI continues to deliver value after hours. In time, AI will level the playing field between SMBs and large enterprises. Those who move first, who rethink work, who redesign experiences, who reimagine leadership, will set the pace for everyone else.

Want to Hear the Full Conversation?

This article only scratches the surface. In the full episode of Practically Tomorrow, Peter and I discuss:

How AI impacts leadership and boardroom dynamics

Why storytelling is the key to inspiring change

How to balance linear growth with exponential innovation

The future of experience design in an AI-powered world

If you’re leading, or aspiring to lead, through this next chapter of technological disruption, I hope this conversation and these reflections give you a new lens to look through.

Let me know what you think, and share the episode with someone who’s ready to move from automation to transformation.

 

Listen now on Spotify

Learn more about my book Mindshift

The post What Happens to Companies That Don’t Think Big Enough with AI? appeared first on Brian Solis.

Designing the AI-Powered Workplace: What Workers Want, and Why It Matters

What do real workers want from AI? And how does that differ from what AI experts think?

Let’s explore an insightful study recently published by Stanford University Social and Language Technologies Lab, “Future of Work with AI Agents.”

Drawing on over 2,100 tasks across 104 occupations, the research compares how workers and AI experts think about automation (what AI should do on its own) and augmentation (where AI should collaborate with humans).

Two groups were surveyed:

1,500 domain workers — the people doing the jobs.52 AI experts — those building the tools.

The results are grounded in O*NET, the U.S. Department of Labor’s job database, and offer a rare task-level view into where humans want to stay involved, and why.

The key takeaway? Workers don’t just want to keep their jobs; they want AI to work with them, not instead of them, especially in areas involving communication, judgment, and human connection. But don’t stop here. There’s so.much.more.

This first visual is a snapshot from a large-scale research effort aimed at answering a critical question:

How do workers and AI experts differ in their views on which tasks should be automated — and which should be augmented by AI?

The study analyzes over 2,100 tasks across 104 occupations, using task-level data to explore two key dimensions:

How much human involvement do workers want in their day-to-day tasks?How much AI involvement do experts believe is technically feasible ?

Two key perspectives were measured:

Automation (blue): Tasks that AI could perform entirely on its own — and how workers feel about that possibility.Augmentation (green): Tasks where AI could assist humans — and the ideal level of collaboration between the two.

The researchers surveyed two distinct groups:

1,500 domain workers — people currently performing these tasks in the real world52 AI experts — technical professionals evaluating AI’s capabilities

Each group was asked:

For automation: Can AI do this task alone? Should it?For augmentation: If AI helps, what’s the right balance between human and machine input?

The findings reveal several drivers behind workers’ preferences:

Job security and enjoyment tend to make workers resist full automation.Tasks requiring expertise, judgment, or interpersonal interaction lean heavily toward augmentation.Physical tasks fall somewhere in between, depending on the nature of the work.

In short, this research highlights the nuanced ways people think about AI — not just as a tool, but as a collaborator, and sometimes, as a competitor.

Over 70 million U.S. workers are on the brink of the biggest workplace transition in decades! And it’s being driven by AI agents.

As technology advances, worker perspectives are too often left out of the conversation.

So, what do workers actually want AI to automate, and where do they prefer human-AI collaboration? Oh, and how do those preferences stack up against what the technology can realistically do?

As part of the study, workers shared their top concerns about AI’s role in their jobs:

45% said they don’t trust AI to handle their tasks responsibly23% fear being replaced entirely16% worry about the loss of the human touch in their work

 

These aren’t just statistics, they’re usable signals. Signals that any future of work built with AI needs to be designed for people, not just for performance or stakeholders or shareholders.

Despite widespread concerns, nearly half of all workers are open to AI automation — under the right conditions.

In the study, 46.1% of tasks were rated positively for full AI automation by the workers who actually perform them. That means nearly half the time, people said they would welcome AI doing the task entirely…even after considering risks like job loss and reduced enjoyment.

This signals a key nuance: workers aren’t simply resistant to AI, they’re open to it when it offloads routine, repetitive, or less meaningful work. As the popular ideology goes, this frees them to focus on what matters more.

The challenge isn’t just what AI can do. It’s what people are willing to let go of…and why. So, so, so, important and under-explored!

Why do workers want AI to automate parts of their jobs?

When workers express a desire for automation, it’s not because they want to do less — it’s because they want to do better.

Among the 3,618 task responses where workers rated their automation desire at 3 or higher (on a 5-point scale), the most common motivations were:

69.4% — Freeing up time for high-value work46.6% — The task is repetitive or tedious46.6% — Automation could improve work quality25.5% — The task is stressful or mentally draining

 

While some also cited tasks being complicated or difficult, the bigger theme was clear: Workers are most open to automation when it relieves low-value, exhausting, or repetitive work, giving them more time and mental space (yes please) for the parts of their job that matter most.

In other words, automation isn’t just about efficiency. It’s about making room for meaning.

Not all tasks are created equal…AND…not all should be automated.

To help guide where AI agent investments should (and shouldn’t) go, Stanford researchers identified four distinct “task zones” based on two key factors:

Worker desire for automationAI expert assessment of technical capability

These zones provide a framework to align technological potential with human values:

1. Automation “Green Light” = Zone High worker desire, high AI capability.

These tasks are ideal candidates for automation. They promise strong productivity gains and broad worker support, making them low-friction wins for AI deployment.

2. Automation “Red Light” = Zone Low worker desire, high AI capability.

Technically, AI can handle these tasks, but workers don’t want it to. Automating here risks resistance, lower morale, or broader social backlash. Caution is advised.

3. R&D Opportunity Zone = High worker desire, low AI capability.

Workers want help here, but AI isn’t ready yet. These tasks point to valuable frontiers for research and innovation, where investment could deliver strong future payoff.

4. Low Priority Zone = Low worker desire, low AI capability.

These tasks are unlikely to benefit from automation in the near term, and workers aren’t asking for it. It’s probably best to deprioritize for now.

Automation vs. Augmentation: Not everything should be fully Handed off to AI

While much of the conversation around AI focuses on automation, Stanford’s research also explored the other side of the equation: augmentation. This is where AI supports, rather than replaces, human effort.

To analyze this, the team introduced a new framework: the Human Agency Scale (HAS).

The HAS is a five-level scale that measures how essential human involvement is for a task to be done well — from H1 (fully autonomous) to H5 (human-led and AI-assisted…if at all).

The HAS centers on human value, judgment, and the need for involvement, even in cases where automation is technically possible.

This shift from an “AI-first” model to a “human-centered” one offers a more nuanced way to decide not just what can be automated, but what should be augmented…and why.

Most workers don’t want AI to take over, they want a partner.

Stanford’s research shows that across many occupations, workers aren’t looking for full automation. I mean, who is!? Instead, they prefer a collaborative relationship with AI, one that balances machine support with human judgment.

On the Human Agency Scale, this balanced view is captured by H3: Equal Partnership, where humans and AI share responsibility for completing a task.

H3 emerged as the dominant preference in 45.2% of occupations (47 out of 104) — making it the most common worker-desired level overall.

Other preferences were:

H2 (AI support with human oversight at key points): 35.6%H4 (Human-led, AI assists most of the time): 16.3%H1 (Full automation): 1.9%H5 (Human-only, no AI): 1.0%

The takeaway? Even as AI grows more capable, workers want to stay meaningfully involved. They’re not asking to be replaced. As if that were a thing! They’re asking for shared control, trust, and agency.

Workers want more control than AI experts think is necessary

As AI capabilities advance, a growing gap is emerging, not in what’s possible, but in what people actually want.

Stanford’s analysis shows that in 47.5% of the 844 tasks studied, workers prefer to retain more human involvement than AI experts believe technically necessary. What this means is that workers are leaning toward higher levels of human agency, even when AI could, in essence, take on more of the task.

This misalignment is clearly visible in the heat map above.

Cells below the diagonal (like H4 worker preference vs. H2 expert feasibility) show tasks where workers want more involvement than AI experts recommend.That red-shaded area (16.4%) highlights just one such region. This is a clear signal of emerging tension.

The implication? As AI gets more powerful, it’s not just a question of what we canautomate, but whether people will trust, accept, and support that automation. And that right there is all about vision and comms.

Designing AI for the workplace means building with human values at the core, not just technical efficiency. But, that’s been true with every technology revolution.

Automation isn’t one-size-fits-all; even within the same job

Different tasks within a single job may require very different levels of human involvement, trust, and judgment, and should not be automated in the same way. 100%!

Take the role of a computer programmer: it’s highly technical, data-driven, and already deeply intertwined with digital tools. And yet, when you break it down task by task, the desired role of AI varies dramatically.

According to Stanford’s study:

For assigning and reviewing work, both workers and experts aligned on equal partnership (H3).For writing documentation, AI experts saw no need for human input (H1), but workers still preferred key-point involvement (H2).For debugging and correcting errors, workers leaned toward equal collaboration (H3), while experts rated it feasible with less human input (H4).

This mismatch shows that even in high-tech roles, trust and control are critical.

If AI agents are deployed in high-agency tasks without human in the loop design, the risks go beyond performance:

Users may reject or ignore the tools.They may override AI outputs entirely.They may feel disempowered and morale will sink, eroding trust and job satisfaction.

AI success depends as much on human alignment as it does on technical capability.

What happens when we value skills by human involvement and not just pay?

This chart above offers a powerful perspective shift: Instead of ranking skills by how much they currently pay, it ranks them by how much human agency AI experts believe they require.

When we compare these two views, 1) economic, 2) human-centered, three key trends emerge:

1. Information-processing skills may decline in relative value

Skills like analyzing data, updating knowledge, and documenting information rank high by wage, but lower in required human agency. As AI becomes better at handling these tasks, their reliance on human input, and their unique value as human work, may shrink. *sigh*

2. People and coordination skills become more essential

Tasks like organizing work, training others, and communicating with peers may not always top wage charts, but they dominate in terms of human involvement. These are skills that resist full automation because they rely on emotional intelligence, situational awareness, critical thinking, and collaboration.

3. High-agency skills are broad, interpersonal, and deeply human

Tasks requiring high human agency span a wide range…from planning and teaching to decision-making and motivating others. They reflect not just what people do, but how they lead, guide, and connect with others.

As AI handles more of the technical, repetitive, or informational work, the skills that will define human value are the ones that machines can’t replicate: Judgment. Empathy. Leadership. Trust.

This is a shift in what we value in work, and in each other.

As AI advances, human skills will matter more than ever

As machines take on more routine, data-driven tasks, the skills that truly differentiate people, collaboration, leadership, communication, and nuanced judgment, will only grow in importance.

To build a future of work that works for everyone, here are three essential takeaways:

1. AI adoption must be task-aware, not job-aware.

Jobs are made up of many tasks, and, not all are created equal. Some tasks within a single role may be ideal for automation, while others require thoughtful human-AI collaboration. Successful AI implementation depends on understanding this task-level nuance.

2. There’s a gap between technical feasibility and worker comfort.

Workers often want more control and involvement than AI experts think is necessary. Ignoring this mismatch could slow adoption, reduce trust, or lead to resistance. Managing that tension is critical. Anticipating it is now an option. And it all must be done with thoughtfulness, transparency, and feedback.

3. Use the Human Agency Scale to guide responsible transformation.

The HAS framework helps organizations identify which tasks should be:

Automated,Augmented,Or left entirely human.

By anchoring AI strategy in human-centered design and empathy, companies can deploy tools and AI agents people actually want to use and work with. This will lead to better adoption, more trust, and more responsible innovation.

Remember…AI doesn’t replace people, it reshapes work. That’s if you want it to. It’s a choice. Let’s make sure it does so in ways that elevate what makes us human and what makes us better with AI and makes AI better with us!

 

 

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Daily Magazine Italia: Scenari Intelligenza artificiale e AI agentica, l’alba di una nuova era

AI Agentica

L’alba di una nuova era, l’analisi di Brian Solis, head of global innovation ServiceNow (Page 60)

Screenshot

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CIO España: La IA supone un cambio de paradigma al exigir a las organizaciones que se replanteen la forma de operar

Por Irene Iglesias Álvarez, CIO España, El antropólogo digital y futurista ahonda en el porvenir de los negocios en un escenario copado por la inteligencia artificial e insta a los CIO a tomar la delantera. Así ha hablado para esta publicación.

Presentado en sociedad como antropólogo digital y futurista, el perfil de Brian Solis bien podría considerarse una rara avis dada su singularidad; sin embargo, en un escenario en el que parecen brotar evangelistas por doquier al abrigo de la digitalización, su figura también podría haberles pasado desapercibida. Precisamente por eso, aprovechando su parada en la capital en el marco de la celebración del evento Put AI to Work Summit 2025 de ServiceNow, CIO ESPAÑA se sentó el pasado mes de abril con el orador de renombre mundial para tomar el pulso a la tecnología que más clamores parece estar levantando en los últimos tiempos: la inteligencia artificial (IA).

El ejecutivo habla con razón de causa, parece sentar cátedra en una conversación que domina con agudeza. Y es que la experiencia es un grado, algo que queda patente al conocer su labor al frente de la compañía de desarrollo de software: el asesoramiento a líderes tecnológicos y empresariales a lo largo y ancho de la geografía sobre estrategias de innovación y transformación digital. Por si esto no fuera un trabajo a tiempo completo, Solis también atesora un palmarés de publicaciones que versan sobre el futuro de los negocios, el trabajo, la digitalización y la innovación en sectores como el comercio minorista, la salud, los servicios financieros, los seguros y el sector público.

Sus trabajos y presentaciones humanizan las tendencias y tecnologías disruptivas y su impacto en las empresas, los mercados y las sociedades. “Hacemos la investigación necesaria para luego aplicar ingeniería inversa o backcasting con el propósito de ayudar a nuestros clientes a tomar decisiones a largo plazo sobre la transformación digital”, explica.

¿Cómo ve el panorama tecnológico actual? ¿Qué impacto diría que tienen las tecnologías emergentes en la sociedad, la industria y la empresa en la actualidad?

El impacto de la tecnología es increíble y maravilloso, pero es mayor de lo que, creo, a la mayoría de las personas les está dando tiempo a comprender. Si pensamos en cada revolución tecnológica de las últimas décadas, las organizaciones las han incorporado tradicionalmente para hacer mejor lo que hacían ayer, y los objetivos han sido la escala, la eficiencia, la optimización, tal vez el aumento de la rentabilidad, todas cosas buenas. Sin embargo, cuando la IA generativa llegó al mercado en 2022, se produjo la misma reacción. Pero ésta, como saben, requiere de datos óptimos para que las organizaciones puedan explotar los conocimientos y las capacidades de la IA.

Esto es importante, anuncia un cambio de paradigma porque, finalmente, hay una tecnología que exige a las organizaciones que se replanteen su forma de operar. Lo que tenemos delante es una oportunidad para que las organizaciones no solo miren a la IA, sino que miren a cada evolución que esta trae consigo, como la IA agentiva, para hacer de su empresa una organización más inteligente. En lugar de adaptar el trabajo del pasado, podemos reinventarlo para el futuro.

Este es el momento más importante no solo para reaccionar, sino también para pensar en estrategias futuras. Hay estudios interesantes que muestran cómo la gente en general se siente abrumada por la tecnología en sus vidas, sienten que pueden no tener el control de la tecnología tanto como la tecnología tiene el control de ellos. Por ejemplo, con las redes sociales, los dispositivos móviles, la IA que potencialmente reemplaza puestos de trabajo… Sin embargo, al mismo tiempo, existe una oportunidad de oro para que las empresas y la sociedad se transformen. Es el momento de que la tecnología trabaje para nosotros.

La inteligencia artificial está de moda, es un hecho incontestable. ¿Cree que su potencial para transformar está a la altura del hype que genera o viviremos un invierno de la IA?

Todas las tecnologías pasan por un ciclo de exageración, como ha radiografiado Gartner, y ciertamente la IA ha alcanzado el pico, pero es de esperar que todas las tecnologías acaben encontrando sus casos de uso para la transformación. Por ejemplo, cuando hablamos de cómo las empresas utilizan las tecnologías para hacer que el mañana sea mejor que el ayer, ahí es donde se ha centrado la IA generativa. Ayuda a la gente a escribir mejores correos electrónicos, mejores presentaciones. Ayuda a los usuarios a obtener un mejor servicio de atención al cliente en términos de autoayuda, pero esa, esa es la historia de la automatización.

Para que cualquier tecnología alcance su verdadero potencial se necesita visión, y la visión es un bien preciado. La visión requiere que alguien entienda el potencial de un caso de uso que no existía ayer para transformar el mañana. Aquí es donde la innovación se vuelve tan poderosa, especialmente con la IA. Creo que se abre un horizonte de maravillosas oportunidades que harán que las personas sean más capaces mañana de lo que eran ayer. Esto significa que la visión requiere definir cuáles serán las habilidades laborales del futuro. El potencial futuro está en la colaboración con la IA, los nuevos resultados que se pueden lograr a través del equilibrio entre el ser humano y la IA. Esta sintonía entre la automatización y la mejora permitirá a las personas, ya sean profesionales en el trabajo o en su vida personal, lograr los tipos de resultados que ayer no eran posibles o que ni siquiera se concebían. Aquí es donde el potencial del que hemos oído hablar con la IA pasará de ser una exageración a una realidad.

Hoy en día todas las empresas tienen una gran oportunidad para inclinarse hacia la innovación. La forma en que defino la innovación es creando nuevo valor. Muchas empresas confunden innovación con iteración, ¿vale? Por ejemplo, ahora estoy usando IA, somos innovadores, pero si nos fijamos en cómo la están aplicando, en realidad es iterativa. La innovación sería el equivalente a hacer algo completamente nuevo para crear nuevo valor. Y creo que estamos pasando del hype a la visión con la IA para crear un futuro que antes no era posible.

“Para que cualquier tecnología alcance su verdadero potencial se necesita visión, y la visión es un bien preciado. Requiere que alguien entienda el potencial de un caso de uso que no existía ayer para transformar el mañana”

¿Cuál es su consejo para los CIO que no quieran quedarse atrapados en la automatización, es decir, que busquen pasar de la iteración a la aumentación y a la innovación?

El futuro para los directores de sistemas de la información pasa potencialmente por añadir innovación a la visión y estrategia empresarial. Este es un momento realmente poderoso para que se desafíen a sí mismos mientras piensan en sus propios roles. El consejo que tengo para los CIO es que adopten lo que llamamos una mentalidad AI first, una filosofía de innovación, que desafíen todas sus convicciones.

Entiendo que los directores de sistemas de información tienen una presión tremenda, más tecnología que nunca, así como tanta tecnología heredada que impide una transformación rápida. Pero si alguna vez hubo un momento para considerar un nuevo futuro, es ahora.

El consejo que tengo para los CIO es que se pregunten qué papel quieren desempeñar en la transformación empresarial de la IA. Porque, históricamente, los directores de sistemas de información se han considerado un centro de costes. Y cuando se te considera un centro de costes, a menudo tus principales métricas son: ¿cuánto coste puedes sacar de la organización?, ¿dónde podemos ahorrar dinero?, ¿dónde podemos optimizar?, ¿dónde podemos racionalizar?, ¿dónde podemos automatizar todas las conversaciones importantes que tenemos? Pero creo que el futuro de los CIO tiene que virar hacia preguntas tales como: ¿cuál es el crecimiento que puedo impulsar a través de las inversiones? ¿Cómo cambio mi narrativa dentro de la organización para no pensar solo en los costes, sino también en impulsar un crecimiento que ayude a nuestra organización a competir en una era de IA a través de la automatización y la mejora?

Se trata de un conjunto diferente de preguntas que abren nuevas oportunidades para la organización, que desbloquean el potencial de la automatización y la aumentación para lograr el crecimiento, lo que creo que transformará el papel de los CIO en roles más influyentes dentro de la empresa a la hora de definir cuál podría ser el futuro de los negocios.

¿Va a cambiar esto la narrativa entre el CIO y los comités de dirección?

Eso espero. Creo que este es un destino que los CIO deben crear para sí mismos. Está en su mano definir cómo se presenta ante la alta dirección y los consejos de administración para defender las inversiones en la transformación de la IA a nivel empresarial, más allá de un simple nivel de transformación heredado. Es un momento muy importante para ellos.

Cambiando de tercio, la IA agentiva parece haberse convertido en la hermana popular de la IA generativa, ¿por qué? ¿Cómo diría que están revolucionando la operativa y la estructura de las organizaciones?

Uno de los retos a los que se enfrentan las organizaciones es que cuando buscan reducir únicamente costes utilizando la IA, comunicar el retorno de la inversión es muy difícil, por lo que las organizaciones se encuentran todavía madurando la forma de implementarla. El pasado mes de mayo publicamos un informe llamado AI Index, que estudiaba el nivel de madurez que tenían las empresas a medida que iban implementando la IA y, en última instancia, transformándose. Tenemos una última versión del estudio que sostiene que las empresas están en una fase muy temprana de madurez. Están en pañales en cuestiones como la gobernanza, la definición de casos de uso, la puesta a prueba de esos casos de uso, la demostración de valor y, por tanto, el potencial de esa transformación.

No obstante, hay que considerar inversiones paralelas y beneficios rápidos como la reducción de costes o los flujos de trabajo interfuncionales que transformarán la organización para ahorrar y escalar aún más, pero también para obtener mejores resultados. Este va a ser un caso de uso diferenciado porque va a liberar a las personas, aumentar la productividad y permitirnos definir los roles futuros ahora mismo. Con un enfoque aumentado, con una mentalidad centrada en la IA, las empresas podrán definir un nuevo valor neto y resultados diferenciados que les ayudarán a desplegar un nuevo abanico de oportunidades.

“El futuro para los directores de sistemas de la información pasa potencialmente por añadir innovación a la visión y estrategia empresarial”

Si a las empresas no les fue del todo bien desplegando pruebas de concepto de IA generativa, ¿qué le hace pensar que tendrán mejor suerte con la IA agentiva? ¿Qué grado de adopción podemos esperar?

Esta es una pregunta importante, realmente creo que es un reflejo de muchas de las diferencias que hemos discutido entre iteración e innovación. Si nos fijamos en investigaciones de Gartner e IDC, se muestra que las empresas no han logrado los tipos de resultados que pensaban que eran posibles con la transformación digital. Se podría decir, por tanto, que estamos viendo los mismos retos con la IA generativa al aplicar la misma mentalidad. En este sentido desafiaría a los CIO y a los demás directivos a trabajar juntos. Tenemos que soñar a lo grande para que la IA logre los tipos de resultados que esperan los comités de dirección en términos de negocio, productividad y competitividad.

El CIO, para cambiar su discurso, tiene que centrarse en los casos de uso que le van a permitir ir un paso más allá, hacer que el negocio sea más eficiente y más eficaz. Así que digo: sueñen a lo grande con los casos de uso que consideren y defiendan su valor más allá de los rápidos beneficios iniciales que las empresas buscan.

Con el punto de mira puesto en el futuro próximo, ¿qué debemos esperar? ¿Qué tendencias marcarán el compás de la innovación redefiniendo el mundo como hasta ahora lo habíamos imaginado?

¿Hacia dónde se dirigirá el futuro en los próximos 10 años? Creo que veremos empresas basadas en IA agentiva poniendo en marcha flujos de trabajo increíblemente eficientes y efectivos, los datos finalmente comenzarán a llegar al core para dar vida a una inteligencia dentro de la organización de formas que no existían antes… Todo esto hay que imaginarlo, por eso es tan importante, especialmente para los CIO, tomar la delantera. Y es que a menudo hablamos del futuro como si fuera algo que está en el horizonte, pero está aquí mismo. Los agentes de IA ya están aquí; y si vamos a generar un mayor retorno de la inversión, si vamos a generar un trabajo transformador, si vamos a impulsar el futuro de los roles para que los empleados prosperen en una era de IA aumentada, este es el momento en el que nosotros, como líderes, tenemos que dar un paso adelante.

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El Periódico: La IA se está comiendo el mundo: la nueva revolución empresarial ya está aquí

El Periódico

Al automatizar procesos repetitivos, la inteligencia artificial permite que los equipos se enfoquen en lo que aporta valor: la creatividad, la estrategia y la resolución de problemas

Hace una década, fue el ‘software’. Según la célebre frase de Marc Andreessen, esta tecnología se estaba «comiendo el mundo» y cambiaría nuestras vidas para siempre.

Ahora, con la Inteligencia Artificial (IA), llega otra revolución. No es solo un avance tecnológico, sino el inicio de una nueva era en la que las empresas pueden desafiar lo establecido, reinventar la manera en que crean valor y transformar su futuro de la mano de clientes y empleados.

En un mundo donde la disrupción marca el ritmo, la IA se ha convertido en un homogeneizador que brinda a todas las organizaciones la oportunidad de romper barreras y liderar la innovación. Imaginemos una pyme que, gracias a esta tecnología, puede ofrecer recomendaciones personalizadas con la misma precisión que los gigantes del comercio electrónico. O un centro médico que utiliza la IA para mejorar diagnósticos y ofrecer tratamientos más eficaces, transformando la atención a sus pacientes. Son solo algunos ejemplos de cómo la inteligencia artificial está nivelando el terreno de juego, democratizando la innovación y abriendo oportunidades antes inimaginables para que todas las empresas, independientemente de su tamaño, crezcan y sean más ágiles.

Lo extraordinario de esta revolución es el poder transformador de la IA para revelar un nuevo valor, que permite a las organizaciones evolucionar de lo rutinario a lo estratégico, de lo reactivo a lo predictivo, y de productos estándar a experiencias personalizadas y escalables, abriendo un mundo de posibilidades sin igual.

La experiencia del cliente es un claro ejemplo. En la era hiperconectada, la personalización ya no es un lujo, sino una ventaja competitiva. Gracias a la IA, las compañías pueden procesar enormes volúmenes de datos en tiempo real para ofrecer experiencias hiperrelevantes a gran escala. Un caso emblemático es Netflix: su motor de recomendaciones no solo mantiene a los usuarios enganchados, sino que también impulsa la producción de contenido y refuerza la fidelización.

La inteligencia artificial personaliza experiencias y, al mismo tiempo, libera a las personas de tareas repetitivas. Al automatizar procesos como la entrada de datos, la gestión de inventarios o la logística, permite que los equipos se enfoquen en lo que realmente aporta valor: la creatividad, la estrategia y la resolución de problemas. No se trata de sustituir empleos, sino de potenciarlos, otorgando más autonomía a los profesionales para asumir desafíos mayores y mejorar la experiencia tanto de empleados como de clientes. No es casualidad que los líderes empresariales destaquen su potencial transformador. Como apunta Bill McDermott, quienes no adopten la IA a tiempo corren el riesgo de quedarse atrás, perdiendo la oportunidad de dar un salto exponencial hacia el futuro.

La IA impulsa la innovación, un pilar clave para prosperar en un entorno marcado por la disrupción y la competencia. Innovar no es solo generar ideas, sino explorarlas, probarlas y perfeccionarlas. Gracias a herramientas basadas en la IA generativa, las empresas pueden conceptualizar, hacer prototipos e iterar a una velocidad que parecía imposible hace una década, acelerando la creación de productos realmente innovadores.

Aquí radica el verdadero desafío (y la oportunidad), en no confundir la innovación con la iteración. La distinción es crucial: la iteración perfecciona lo existente, mientras que la innovación genera un valor completamente nuevo. En la inteligencia artificial, la automatización corresponde a la iteración. En cambio, la verdadera innovación surge de la sinergia: la capacidad de que humanos y máquinas trabajen en conjunto para alcanzar resultados más complejos, con un valor exponencial en comparación con lo que una entidad por sí sola podría lograr.

En 1983, Steve Jobs predijo que el ordenador se convertiría en el principal medio de comunicación, transformando la relación entre humanos y tecnología. Aunque al principio el PC seguía siendo una herramienta limitada, comparable a los primeros televisores que solo replicaban programación de radio, Jobs anticipó que pronto empoderaría a los usuarios, permitiendo crear contenido. De manera similar a la ‘sinergia’ de hoy, Jobs vislumbró una nueva era en la que la tecnología no solo mejoraría lo existente, sino que abriría nuevas posibilidades.

Lo mismo ocurre en la actualidad con la IA. Todavía la utilizamos como las tecnologías anteriores, automatizando tareas digitalizadas en lugar de replantearnos cómo trabajamos. Es una “mentalidad de control de gastos”, que considera la IA solo como una herramienta para reducir costes, en lugar de reconocerla como un motor de crecimiento exponencial.

Su verdadera innovación, en cambio, va más allá de automatizar tareas; implica adoptar un pensamiento lateral y redefinir la forma de trabajar. Aquí es donde entra el agente de IA: no solo ejecuta tareas, sino que aprende, se adapta y toma decisiones estratégicas de manera autónoma. Al optimizar procesos y sistemas en tiempo real, abre nuevas posibilidades para transformar la manera de operar y tomar decisiones.

Esto cambia por completo las reglas del juego, permitiendo a las organizaciones aumentar la creatividad, adaptarse de manera dinámica a mercados cambiantes y liberar el potencial humano como nunca antes.

Siguiendo la comparación de Steve Jobs entre los nuevos medios y los anteriores, el agente de IA transformará la automatización de flujos de trabajo derivados de la digitalización de procesos tradicionales. Esto permitirá repensar cómo hacer las cosas, creando flujos innovadores impulsados por la IA. En resumen, no se trata solo de ser más eficientes, sino de aprender a reinventar.

La inteligencia artificial ya no es una opción; cambiará nuestras vidas como lo hicieron internet y el móvil. Ahora, la pregunta que cada empresa debería hacerse es si su enfoque está en la innovación o solo en la iteración. Solo aquellas que adopten la IA con curiosidad, valentía y el compromiso de explorar lo desconocido prosperarán; las otras quedarán atrás.

Vivimos una transformación en la que ya no basta con reaccionar. Es necesario un cambio de mentalidad para liderar con audacia e innovar sin miedo. La IA está transformando el mundo, ofreciendónos oportunidades inéditas.

Esta tecnología es el futuro, y ese futuro ya está aquí. Es hora de redefinir las reglas de la innovación, y no podemos esperar. La inteligencia artificial ha llegado para quedarse y solo quienes aprovechen su poder liderarán una nueva era de posibilidades.

 

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Industria Italiana: L’IA agentica è un’opportunità che non si può rischiare di perdere. Parola di ServiceNow

Riceviamo e pubblichiamo integralmente un articolo a cura di Brian Solis, head of global innovation di ServiceNow, Industria Italiana

La rivoluzione dell’intelligenza artificiale non è solo un altro capitolo della storia della tecnologia, ma l’inizio di una storia completamente nuova. Una storia in cui le aziende possono reimmaginare ciò che è possibile, ripensare la creazione di valore per un mercato in evoluzione e rimodellare il proprio futuro insieme a clienti e dipendenti.

In un mondo in cui la disruption sembra essere diventata la norma, l’IA è un grande equalizzatore. Immaginate un piccolo rivenditore che sfrutta l’IA per offrire suggerimenti personalizzati alla pari dei giganti dell’e-commerce o un fornitore di servizi sanitari che utilizza l’IA per migliorare gli esiti dei pazienti con una diagnostica di precisione. L’IA sta livellando il campo di gioco, democratizzando l’innovazione, sbloccando possibilità prima irraggiungibili e spalancando le porte della crescita e dell’agilità.

L’era di un nuovo valore

Ciò che rende questa rivoluzione così straordinaria è la capacità dell’AI di aiutare i leader con una mentalità creativa e aperta a scoprire un valore che non sapevamo nemmeno esistesse. Permette di passare dal banale al rilevante, dalla reattività alla predittività, dalla staticità alla dinamicità, da prodotti uguali per tutti a esperienze profondamente personali e scalabili.

Pensiamo per un attimo alla customer experience. Nel mondo iperconnesso di oggi, la personalizzazione non è solo un qualcosa di piacevole, ma è un vantaggio competitivo. L’intelligenza artificiale è in grado di elaborare enormi quantità di dati sui clienti in tempo reale, consentendo alle aziende di offrire esperienze iper-rilevanti su scala. Il motore di suggerimenti di Netflix, per esempio, è la colonna portante della produzione di contenuti e della fidelizzazione dei clienti.

Allo stesso tempo, l’AI può liberarci dalle attività più ripetitive. Automatizzando le attività più banali, come l’inserimento dei dati, la gestione dell’inventario, la logistica, consente alle persone di concentrarsi su ciò che conta davvero: creatività, strategia e risoluzione dei problemi. Non si tratta di sostituire i posti di lavoro, ma di elevarli. I team sono in grado di affrontare sfide più importanti, che portano a dipendenti e clienti più impegnati e soddisfatti.

Alla conquista dell’innovazione

Bill McDermott, presidente e ceo di ServiceNow, ha recentemente affermato che “l’AI è la più grande opportunità del nostro tempo”. Le aziende più lente e avverse al rischio che adottano un approccio attendista nei confronti dell’AI danno ai concorrenti non solo un vantaggio, ma una vera e propria possibilità di sorpasso.

“I ritardatari e i negazionisti in materia di AI subiranno un’enorme perdita”, ha avvertito McDermott.

L’intelligenza artificiale potenzia l’innovazione, che è fondamentale per affrontare un mercato e una concorrenza in continua trasformazione. Ogni innovazione inizia con l’esplorazione e la sperimentazione. Grazie a strumenti come l’IA generativa, le aziende possono concettualizzare, prototipare e testare e iterare a una velocità che un decennio fa si poteva solo sognare. Immaginiamo di sviluppare prodotti che non si pensava fossero possibili o che non si potevano concepire.

Ma ecco la sfida e anche l’opportunità: molte aziende confondono l’iterazione con l’innovazione. Qual è la differenza? L’iterazione migliora qualcosa di esistente. L’innovazione crea un nuovo valore netto. In un mondo di IA, l’automazione è l’equivalente dell’iterazione. Qual è la correlazione con l’innovazione? Per quanto riguarda l’IA, è augmentation, la capacità di umani e macchine di collaborare per ottenere risultati più grandi ed esponenziali di quelli possibili da parte di una sola entità.

Nel 1983, Steve Jobs aveva previsto che i personal computer sarebbero diventati onnipresenti e sarebbero diventati il principale mezzo di comunicazione. Predisse anche che all’inizio avremmo “sbagliato modo di usare i computer”, paragonandoli alla prima generazione di televisori che fornivano contenuti visivi che all’epoca erano essenzialmente programmi radiofonici ripresi da una telecamera. “Quando un nuovo mezzo di comunicazione entra in scena, tendiamo a farlo rientrare nelle vecchie abitudini”, ha spiegato.

Ha poi parlato di tutte le capacità che un personal computer avrebbe sbloccato, trasformando gli utenti di computer di tutti i giorni in artisti e trasformando le comunicazioni lungo il percorso. Lo stesso vale per l’IA.

Oggi usiamo questo nuovo strumento nel nostro lavoro nello stesso modo in cui abbiamo utilizzato lo strumento di ieri. Stiamo ancora automatizzando il lavoro di ieri che abbiamo digitalizzato negli sforzi di “trasformazione digitale” di ieri, invece di reimmaginare il lavoro per ciascun mezzo. Le aziende sono in gran parte bloccate nella “mentalità del centro di costo”, utilizzando l’AI per tagliare le spese invece di investire in aree che possono generare un valore esponenziale.

La vera innovazione richiede un cambiamento di mentalità. Si tratta di aprire la mente, concedersi il permesso di essere più curiosi e creativi, mettere in discussione le ipotesi e chiedersi non solo come fare le cose in modo migliore o meno costoso, ma anche come farle in modo diverso.

L’ascesa dell’AI agentica

È qui che la situazione si fa davvero entusiasmante: la nascita dell’IA agentica. L’IA agentica apprende, si adatta e agisce in modo autonomo. Questi agenti non si limitano a eseguire compiti, ma orchestrano sistemi complessi, lavorano insieme, ottimizzano i processi in tempo reale e prendono persino decisioni strategiche… e imparano da queste decisioni per migliorare il processo decisionale.

Perché questo è positivo per le imprese? Perché cambia radicalmente le regole di ingaggio. L’IA agentica permette alle organizzazioni di scalare la creatività, di adattarsi dinamicamente ai mercati in evoluzione e di liberare il potenziale umano in modi mai visti prima.

Immaginate gli agenti dell’AI che gestiscono le catene di approvvigionamento, ottimizzano i viaggi dei clienti o addirittura guidano l’innovazione esplorando le idee, il tutto coinvolgendo un essere umano, ma muovendosi più velocemente e su scala.

Rivediamo il rapporto tra iterazione, innovazione e automazione e il paragone di Steve Jobs tra un nuovo mezzo e il mezzo precedente. L’ascesa dell’IA agentica può, e molto probabilmente lo farà, collocare gli agenti all’interno di workflow automatizzati che sono stati digitalizzati da predecessori analogici. Allo stesso tempo, gli innovatori riconsidereranno il lavoro stesso per immaginare nuovi workflow verso risultati iterativi e innovativi che l’IA e l’IA agentica catalizzano.

Non si tratta più solo di efficientare, ma di reinventare.

Abbracciare l’inevitabilità e conquistare le possibilità dell’IA

L’IA non è un optional. È inevitabile come lo era Internet e come lo sono stati la telefonia mobile e i social media. L’unica domanda da porsi è se la si abbraccerà con la mentalità dell’iterazione o con quella dell’iterazione + innovazione. Le aziende che si avvicinano all’IA con curiosità, coraggio e impegno nell’esplorare l’ignoto prospereranno rispetto a quelle che, come ha descritto Steve Jobs, usano il nuovo strumento come utilizzavano il precedente.

L’IA è il futuro, e quel futuro si sta dispiegando ora. La rivoluzione dell’IA non sta solo bussando alla porta, ma invita a riscrivere le regole. Questo è il momento. Non bisogna aspettare che sia qualcun altro ad aprire la strada, perché è probabile che questo porti dritti verso l’iterazione. È il momento di essere leader di cui hanno bisogno i clienti, i dipendenti e la propria azienda. L’intelligenza artificiale è qui per restare e per coloro che sono pronti a sfruttare la potenza dell’automazione e dell’augmentation, il futuro è esponenziale.

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CIO: Is declining AI maturity a sign of progress?

Dave Wright, Rachael Sandel, Brian Solis

via CIO Online, Dave Wright and Brian Solis

At first glance, the central finding in the newly released ServiceNow and Oxford Economics’ 2025 Enterprise AI Maturity Index study seems surprising: on a 100-point scale, the average AI maturity score dropped nine points from last year. With so much attention, focus and investment in AI, how is it possible that businesses have fallen behind?

The reasons are relatable but telling. The speed of AI is overwhelming and moving faster than most organizations can keep up. In 2022, OpenAI introduced the world to generative AI. By 2024-2025, AI agents took over the spotlight. Now, agentic AI is the new rage. At the same time, AI complexity combined with the uncertainty around unproven pilots and the inherent limitations of basic use cases is holding back companies around the world, and across every industry. Naturally, they’re more reserved and move cautiously.

There are also those leaders who see uncertainty as a catalyst for finding answers and an opportunity for curiosity, exploration and imagination. This group is motivated to speed up, to challenge their assumptions and explore bolder, more ambitious pilots that move the needle. In doing so, they broaden their perspectives and force-function the ability to uncover more impactful AI use cases and outcomes. ServiceNow calls these progressive leaders AI Pacesetters.

AAt first glance, the central finding in the newly released ServiceNow and Oxford Economics’ 2025 Enterprise AI Maturity Index study seems surprising: on a 100-point scale, the average AI maturity score dropped nine points from last year. With so much attention, focus and investment in AI, how is it possible that businesses have fallen behind?

The reasons are relatable but telling. The speed of AI is overwhelming and moving faster than most organizations can keep up. In 2022, OpenAI introduced the world to generative AI. By 2024-2025, AI agents took over the spotlight. Now, agentic AI is the new rage. At the same time, AI complexity combined with the uncertainty around unproven pilots and the inherent limitations of basic use cases is holding back companies around the world, and across every industry. Naturally, they’re more reserved and move cautiously.

There are also those leaders who see uncertainty as a catalyst for finding answers and an opportunity for curiosity, exploration and imagination. This group is motivated to speed up, to challenge their assumptions and explore bolder, more ambitious pilots that move the needle. In doing so, they broaden their perspectives and force-function the ability to uncover more impactful AI use cases and outcomes. ServiceNow calls these progressive leaders AI Pacesetters.

What does it mean to be low or high in AI maturity?

The study measured organizations across five pillars of maturity:

AI strategy and leadershipWorkflow integrationTalent and workforceAI governanceRealizing value in AI investment

Early enterprise maturity starts when companies begin to understand AI and explore how it can be used in their company, whereas full maturity involves transformation, when a company’s AI vision is focused on innovation and transformational investment.

The decline in AI maturity found in the 2025 Enterprise AI Maturity Index illustrates that, across the board, companies are struggling to keep up with the pace of change. In further studying the data and speaking with companies, we also know that they’re constrained by the limited use cases and examples of companies bucking the trend and breaking ground. As a result, the vast majority of businesses are in the early stages of AI maturity.

The decline in maturity also speaks to a reality check across companies. The relentless focus and hype around AI pressured everyone to act on the technology and behave as if they knew exactly what they wanted to do with it. But as AI keeps advancing and agentic AI has opened up ever more possibilities, executives are realizing they aren’t fully sure what they want to do with AI.

This all comes with a huge upside: It’s still early and it isn’t too late to make progress.

Learning from an AI Pacesetter

So, if we know AI has the potential to transform lives, work, businesses and markets, but we also recognize how much needs to be done to realize the opportunities, then what are executives to do? Some companies are more advanced in their AI maturity, offering a practical roadmap. These AI Pacesetters scored nine points higher in maturity and were far more likely to report improved experiences, efficiency and faster innovation from their AI solutions.

To learn what pacesetters are doing differently, we spent time with Rachael Sandel, the group chief information officer at Orica. Sandel and her team recently won a ServiceNow 2025 Pacesetter Award for their efforts in leading AI advancements. In our conversation, she identified seven steps that were crucial to Orica’s AI approach:

Embed and align your AI strategy with your existing technology and innovation strategies rather than starting from scratch. Instead of a standalone AI strategy, align your AI strategy to your technology roadmap and focus on incorporating AI into the various technology streams and functions. This alignment supports the delivery of collective objectives, including safety, productivity and sustainability.

Modernize your technology platforms to create a solid foundation for taking advantage of AI.

Form separate AI groups with distinct members so you can ensure key AI responsibilities are handled while concentrating your organization’s AI skills, knowledge, decision-making and oversight. These groups should include:

A dedicated AI Center of Excellence with cross-business representation that leads AI thought leadership, evaluating and prioritizing ideas.An AI Council of senior leaders who are focused holistically and high level on risk, policies, initiatives and decision-making.

Prioritize governance by establishing principles and guidelines in alignment with your core values; implementing a governance framework with a group standard and risk management approach; and establishing three separate lines of governance through the AI Center of Excellence, AI Council and internal audits.

Promote talent in AI by hiring curious and adaptable individuals while providing training and upskilling opportunities; consolidating skills into the AI Center of Excellence; and combining talent change with management change to help adapt to technology changes. People will have to learn to work with this technology differently, as well as adjust to different processes and operating models.

Imagine and plan for the future of work with AI agents by extending pilot projects and integrating AI agents into business systems to boost productivity and demonstrate value today. At the same time, prioritize imagining and planning for a future where there is widespread adoption of AI solutions to transform business processes and AI agents perform tasks alongside humans, orchestrating across platforms and data sources and collaborating with other agents, transforming how we work.

The steps Sandel describes focus on creating a solid foundation in terms of technology, people, governance and leadership. Following these steps can help an organization fully harness AI’s potential while navigating the risks and complexities resulting from a technology revolution accelerating at an unprecedented pace.

From an AI strategy to a transformation strategy

Today, most businesses are focused on familiar strategies, with AI added to the remit. How are we going to implement AI in our work? How can I use AI to automate repetitive tasks, summarize activities and spotlight more relevant results? How can I use it to deflect calls, optimize my supply chain, improve vendor or employee onboarding, etc.? But the questions that Sandel and the Orica team are asking look beyond the status quo and instead seek to solve real problems, drive transformation and achieve business impact. AI should be a tool to achieve an organizational vision rather than deploying AI for its own sake. And that starts with having and articulating a ‘visionary’ vision.

When we imagine this bigger strategy, we should be open to questioning everything and recognizing that the full potential of AI will not happen without true transformation. And that transformation starts from within. There is a significant, measurable difference between “having a vision” and “being visionary.” The latter involves questioning why something should be done, not just how we do it. Where we will end up on this AI maturity journey depends on going beyond the constructs of today with AI to augment work and unlock new levels of innovation.

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InformationWeek: The End of Business as Usual – How AI-Native Companies Win

via InformationWeek

AI-native companies aren’t just automating — they’re rearchitecting business. Success requires embedding AI into strategy, decision-making, and workforce evolution.

As AI continues to evolve, the question becomes whether companies can transform their businesses while adapting their workforce strategies at the same pace. An executive mindset shift — or — is needed to not only reimagine businesses forward, but to also prepare workers for roles that don’t yet exist. Seismic shifts lie ahead: artificial intelligence will reshape 86% of businesses by 2030, according to a new World Economic Forum (WEF) . That same report also predicts that AI and automation will create 170 million jobs, while displacing 92 million roles as companies adapt to technological change; 39% of existing skill sets will become outdated between 2025-2030.

Business, Not Digital, Transformation Is the Way Forward

Companies now face a new chapter in the evolution of digital transformation, one that challenges organizations to think beyond the digitization of legacy processes and workflows they prioritized over the past decade. In reality, BCG research uncovered that 70% of digital transformations still fall short of their objectives.

Before the dawn of ChatGPT, it could be argued that most digital transformation efforts focused on the digitization and optimization of legacy processes. The pursuit of efficiency, scale, and cost-cutting limited or impaired the prospect of any meaningful transformation desired business outcomes. The same may already be happening in an era of AI. Companies are prioritizing the automation of the processes and workflows digitized over the past decade, which is important, but without exploring the potential for new opportunities in an era of AI, automation may not be enough to evolve.

I f digital transformation was the defining strategy in the 2000s, AI-native business transformation represents a potentially better, and more adaptable way forward.

Unlike digital transformation, AI represents an opportunity for business transformation. It’s an inflection point to reimagine organizations and work in a world where AI becomes inherently attached to almost every technology, action, and outcome.

The Next Chapter of AI-Native Businesses

2025 is set to be the year that not just AI, but AI agents, start to reshape the enterprise. While organizations are just beginning to recognize the possibilities of AI, they are not yet exploring the implications of businesses that accelerate AI-first transformation. Now is the time for organizations to embrace AI beyond tools and as a core component of their strategic mindset and operational framework.

But what does it mean to be an AI-first enterprise?

To help, let’s substitute AI-first with AI-native: AI as being native to the core of the business itself, strategy, operations, culture, and value creation.

It’s also more than the implementation of AI tools across the enterprise. It’s about redefining roles, work, and operations, fostering innovation, and creating a culture that embraces change. An AI-native enterprise is characterized by the strategic integration of artificial intelligence at the core of its operations and decision-making.

n AI-native approach will fundamentally redefine how businesses operate, innovate, and engage with customers, employees, and their ecosystem. AI becomes not just a tool, but the central driver of decision-making, operational efficiency, and customer interaction.

Lead in the AI Revolution or Be Left Behind

AI-first is not just about using AI, it’s about making AI native to business architecture, foundationally.

1) Make AI core to decision-making: AI is not just a tool for efficiency; it plays a central role in strategic decision-making, forecasting, and autonomous execution.

2) Use AI to drive exponential thinking, not incremental optimization: Instead of improving traditional business processes, AI-native companies reimagine workflows, value chains, and customer experiences from scratch.

3) Automate adaptability: AI-first companies build systems that can sense, analyze, and act autonomously in real-time across supply chains, operations, and customer engagement.

4) Integrate AI to spur network effects and self-learning models: Continuously improve via feedback loops, fine-tune AI models, and leverage collective intelligence rather than relying solely on human input.

5) Make data and compute as a core asset: Unlike traditional companies that prioritize physical assets or human capital, AI-first organizations treat data, compute power, and algorithmic capabilities as their primary competitive advantage.

6) Drive workflow transformation with AI agents: AI agents are the next major evolution in AI-native businesses. They don’t just enhance workflows; they autonomously execute tasks, make decisions, and optimize operations at a scale and speed impossible for human-led organizations. You need to make sure you are designing and enhancing workflows of the future, not the past. Why? AI-native businesses will rely on agentic systems to manage core functions, drive efficiency, and create new competitive advantages.

7) Redefine leadership for an AI-native era: C-Suites are not immune. Train executives and managers to think strategically about AI adoption, guiding their teams in AI-first decision-making and workflow transformation.

8) Invest in reskilling programs for emerging roles: As AI automates repetitive tasks, new roles will emerge that require human creativity, problem-solving, and oversight. Companies must proactively explore and identify future job needs and provide pathways for employees to transition into high-value roles. This includes preparing for an agentic enterprise and beyond.

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