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Innolead Interviews Brian Solis: Using AI to Support Innovation (and Iteration) at ServiceNow

Every company says they “do AI.” Few can show meaningful outcomes.

We’ve been intentional about iteration and innovation. Iteration makes yesterday’s work more efficient. Innovation creates new value. When you separate the two, you can measure cost takeout and progress…and prioritize what matters.

If you’re leading transformation, ask: are your AI investments making yesterday cheaper…or creating tomorrow’s value?

Please read this awesome piece by Dawn Kawamoto for InnoLead and let’s talk about where your org sits on the AI iteration–innovation curve.

Using AI to Support Innovation (and Iteration) at ServiceNow

Since its founding in 2004, Silicon Valley-based ServiceNow has been all about automating business workflows. So in the current AI era, the $11 billion company is focused on how various types of AI will support that automation. Often, ServiceNow’s own employees are “customer zero” for new offerings — early adopters for the products and services it builds.

Already, the company’s AI strategy is helping to reduce service volume by 40 percent, and generating millions in annualized value from AI agents that provide support to its 8,400 global customers.

Brian Solis, Head of Global Innovation at ServiceNow and author of the recent book Mindshift, recently spoke with InnoLead about the software-as-a-service giant’s deployment of AI; the results it’s producing; and the importance of defining both “iteration” and “innovation.”

Can you tell me about your role and how it’s defined?

We have a unique office here. The innovation office is led by my boss, Dave Wright, our Chief Innovation Officer, and my job is to lead a group of what we call innovation officers and futurists in helping our customers and ourselves navigate all these disruptive trends and opportunities, especially now in an era of AI.

We also publish original research and thought leadership inspired by countless conversations with executives on the questions they have, the difficulties and challenges they’re trying to navigate, and also the opportunities that they may not see. Things are moving pretty fast, and it’s easy to react rather than plan ahead, so all that research and thought leadership is published. We’re now occasionally publishing it externally, and we’re also publishing internal-only insights for our executives to help them navigate these trends.

How is AI and GenAI being used at ServiceNow?

What’s really interesting about ServiceNow is that we actually use our stuff, so that we can be “customer zero.” We have an organization within ServiceNow called Now on Now, which tells the ServiceNow story of how we utilize our products.

For example, with GenAI and, especially, AI agents, we utilize our agentic workforce. We’re using AI agents to resolve service tickets, apply system patches at scale proactively, and provide summaries to our human IT managers. And when it comes to scaling software provisioning for our 27,000 employees, it’s a prime opportunity for AI and AI agents.

What impacts have you seen from your internal use of AI and GenAI at ServiceNow?

We’ve actually automated 97 percent of our provisioning requests and reduced service volume by 40 percent. We’re also using AI agents in customer support, which is an interesting use case because it demonstrates what we believe the story around AI needs to be — annualized value from AI agents, and we’re already realizing $350 million. But more importantly, when we can automate the routine, we’re freeing up our human agents to spend more time with customers in realizing value from their investments.

As you journey further into AI and GenAI, what are some of the challenges you are working through?

If you consider how our company has grown over the past couple of decades, the platform we built from the very beginning was the challenge we faced then and still face today. That challenge comes from the legacy mindset companies have about software. Over the years, technology, data, and workflows have become beholden to silos. And now with AI, which feeds on data, it is as effective as the platform it runs on.

The challenge and opportunity for ServiceNow is to help change the mindsets of today’s organizational leaders to recognize that when they see studies like MIT’s, which says that 95 percent of AI investments aren’t realizing value, it’s because of the human capacity for implementing pilots within modern constructs.

For example, when our innovation office works with customers and a company has done something incredibly promising with generative AI, we’ll ask, “Is this pilot to make what you did yesterday better, more efficient, more scalable, or less expensive?” If so, that’s iteration. Innovation is doing what you didn’t do yesterday to create new value.

An innovative pilot on a platform connects the organization, allowing work to move across the enterprise through a system that not only accomplishes tasks or outcomes but also connects data, various systems, and disparate data to gain insights into that work, workflow, and opportunities for optimization. That platform mindset is the challenge and opportunity we’re working on, because we want companies to finally see that after all these years of saying we need to break down silos, that one, you can, and two, you need to.

What percent of companies are instilling an innovative mindset, and what speed bumps are they having to deal with when using AI and GenAI?

Our innovation office created a methodology and a maturity model that we call the AI Index. What we did was study how companies were and weren’t evolving with AI and where the more advanced companies were doing things differently than other companies. For example, the more innovative companies are creating AI innovation centers, not just innovation centers. AI innovation centers combine a center of excellence with a group of internal and external advisors who accelerate cross-functional pilots, so they’re not just locked into one part of the business. They’re not just learning about the technology, but everything that goes around it.

We identified five stages of AI maturity, and only 18 percent of companies are doing more innovative things than their peers. But compare that to a McKinsey study, which found that among all companies investing in AI for potential innovation, only one percent feel they are mature in that regard. An Axios study showed that 90 percent of C-suite executives say that their company has an AI strategy, but only 57 percent of employees agree.

It comes back to that balance between innovation and iteration. If you create a framework that defines what makes iteration and what makes innovation, and you assess those investments, you can then quantify whether the organization is innovative or iterative. When leaders see this is not as full as they’d like, this creates a sense of urgency. They want to learn how to be more innovative.

How do you build a culture of innovation? First, you have to recognize that you don’t have one, and second, you have to understand how people and behaviors, norms, vision, and future motivational states are articulated towards where an organization is going, and where I can see myself as an employee contributing to that. In that last part, most companies do not have innovative cultures, and therefore, they’re not as innovative, but they can be.

When it comes to the future of AI and GenAI, what’s your vision of how it will change business over the next three years?

As a practicing futurist, there was a time when I had to look out 10 years, and it’s getting harder, especially how fast we’re moving. I think what we’re finally going to see is not only the breakdown of silos within organizations, but actually the integration of AI agents with people to automate and augment the work. Augmentation is the opportunity for the future of work.

Over the next three years, on the augmentation side, we’ll see humans and AI working together to accomplish net new types of outcomes. Think about it as a visual metaphor of you trying to push a big rock up the hill, which was impossible before, but now you have this big AI robot helping you push it up. It’s almost like a superpower to unlock new capacities and capabilities.

With this new future of work, we’ll invent new workflows to improve the performance of the organization. Legacy organizations, for example, will not only use automation to make yesterday’s value proposition more efficient to market, but also unlock new value creation for the company to deliver new relevance due to that new human-AI capacity.

Those new workflows will be fascinating because they’ll involve an orchestration of human employees who can perform new types of work with AI, as well as be augmented by agents. Maybe it’s not in three years, maybe it’s five years.

And looking more broadly at infusing an innovative mindset among the workforce, what are the greatest challenges leaders face and — more importantly — what are the workarounds for these challenges?

One of the most difficult truths about innovation is that its primary obstacles are often human rather than technological in nature. Fixed mindsets are baked into how we’ve been taught to lead, manage, and measure progress. If you zoom out and look across most organizations, what you’ll find is that innovation isn’t lacking because people don’t have ideas. It’s lacking because the system around them is designed to optimize for predictability, efficiency, productivity, and other “knowns,” not possibilities or unknowns.

There’s a kind of unconscious bias embedded in many leadership playbooks, legacy thinking inherited from an industrial era. Stability was rewarded, and risk was averted. Scale and efficiency drove strategy and operations, and R&D supported those efforts. As a result, leaders have become more focused on quarter-to-quarter performance, with an emphasis on responding to today’s threats and opportunities. This means that many leaders are not looking…to future-proof their organizations and adapt to these emergent trends as part of the day-to-day innovation needed to out-compete their peers.

Mindshift | Newsletter | Speaking

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Are You Focused on the AI Bubble or the AI Bomb? The Gap That Defines Our Future.

Sitting here at the Wharf in Sydney, thinking about the AI bubble and executive short-termism vs. waves of evolving scenarios where AI and agentic (and eventually autonomous) workflows change business, and societal, trajectories.

This was an interesting analysis on the current state of AI by Shakeel Hashim. His post, “We’re All Behind the Curve,” highlights a critical, often missed gap that determines who gets ahead and who gets left behind.

After speaking at the Curve Conference, he observed two distinct groups. Here’s how he described it, “I wrote about the very scary disconnect I felt between the conversations I was having…and the way the wider world talks about AI.”

The Curve is “where thinkers grapple with AI’s biggest questions, exploring disagreements and building bridges towards solutions.”

While one group focuses on the Hype Cycle and worries about the circularity of investment, market valuations, and whether the economy can survive an AI crash, the other group, working at the frontier of AGI, is grappling with fundamentally different, potentially game-changing questions…

The circularity of recursive self-improvement.

The impending culture war over AI personhood.

The risk of a US regime change driven by AI advances.

Whether democracy can survive the leap.

The focus on the economic alarm bells is generally an unproductive distraction, but I get it. The fear of a bubble-pop and its impact on the economy draws a visceral reaction by those still reeling from the last economic disaster. At the same time, waves of AI impact will change how we work and who or what we employ and why. It’s also helpful to listen to people with “situational awareness” of subjects we may not follow, understand, or care to understand.

If your strategy is still centered on navigating the next hype cycle phase, you are behind. The gravitas of this moment demands we immediately pivot from worrying about quarterly returns to solving problems like space governance and the future of human agency (and the future of people in an agentic or even autonomous enterprise).

Crash or not, the challenges over the horizon can eclipse anything we’ve faced. We are not spending nearly enough time exploring potential scenarios, and as a result, we are not preparing for alternate trajectories or futures.

This is the moment for a strategic mindshift. Join me in reshaping the future..

Subscribe to my newsletter, “A Quantum of Solis.”

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What Sets AI Pacesetters Apart? An Executive’s Guide To Advancing Enterprise AI

From 2023-2024, I studied how companies were and weren’t evolving in their adoption of generative AI. That research led to a framework for tracking enterprise AI maturity across eight pillars:

Vision and StrategyLeadershipData GovernanceAI GovernanceTalent, Skills, and DevelopmentWorkflowsResponsible AIMeasures

In partnership with Richard Murphy and René Stranghoner, we turned a large and complicated spreadsheet into what ultimately became the ServiceNow AI Index. Launched initially in 2024 and again in 2025, we now have two years of insights that offer an idea of how companies are evolving, with some starkly maturing faster than others. We call these faster-moving companies AI Pacesetters.

To help other companies follow in the paths of their peers, we analyzed their steps and what they do differently. The result is this AI Pacesetter Playbook published in Forbes.

There’s a big difference between having a vision and being visionary. It all comes down to why you should do AI rather than how you should do AI,” ServiceNow Chief Innovation Officer Dave Wright told customers in May at the Knowledge 2025 event in Las Vegas.

Pacesetters understand this nuance better than most. They have a vision for what they want their organizations to achieve and use AI as a tool to get there.

Here’s what they do differently…

Lead With An Innovation Mindset

While ingenuity gives pacesetters an edge, not all companies are set up for out-of-the-box thinking.

“For years, we have been taught to follow the rules to achieve goals — to not challenge convention,” Brian Solis, head of global innovation at ServiceNow, said at Knowledge. “Companies are meant to operate efficiently and meant to scale. They fight against risk.”
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But AI is challenging the very nature of what it means to be an organization, he continued. Pacesetters are recognizing this shift and building AI innovation centers to nurture creativity.
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Thinking expansively led a major insurance business to improve IT productivity and accelerate the creation of its service catalog. Each item in such a catalog — like installing a software patch — usually has a multi-step workflow. Using ServiceNow tools, the company automated some of the most significant ones for the first time.
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When companies don’t have the option to dedicate more people or investment to fix a problem or chase an opportunity, they can turn to AI to identify smarter ways to deliver services.

56% of AI pacesetters strongly agree they are operating with an AI vision that is clear and shared,
compared with 30% of others.

Take a platform approach

Pacesetters realize that consolidating departments onto a common platform unites teams, collapses information silos and fuels innovation, Wright said. It decreases the costs of harnessing and accessing data and instead enables employees to focus on the actual tasks at hand.

66% of AI pacesetters use an enterprise-wide platform with built-in AI capabilities, compared to 46% of others.

Focus on talent – Expand Your Hiring Criteria Beyond Technical Ability

Organizations require technical expertise to understand how to build models. But they also need creative thinkers who can use AI to solve customer problems. Increasingly, tools like Now Assist, which is part of the ServiceNow platform, are making it easier to build autonomous chatbots, request summaries and code without dev expertise.

50% of pacesetters agree they have the right mix of talent to execute their AI strategy
compared with 29% of others.

Prioritize AI governance – Set Clear Rules, And Your Employees Will Thank You

Clear risk management guidelines help employees understand what the rules are, said Rachael Sandel, chief information officer at Orica. In 2024, the company released its own AI guidelines that aligned with industry standards and company values.

63% of pacesetters have created AI-specific policies and addressed needs in data governance and security,
compared with 42% of others.

Integrate Agentic AI

Agentic AI — a type of artificial intelligence that acts autonomously to meet defined goals — has had barely a year to get out the gate, but it’s already delivering ROI for early adopters. According to the ServiceNow report, 55% of enterprises using agentic AI said it has already improved gross margins.

36% of pacesetters are using agentic AI, compared with 19% of others.

If you parse through the data, you’ll also see that they invest in a culture, or at least centers, of innovation.

Please read the playbook to learn what you can do differently, starting tomorrow.

As ServiceNow CEO Bill McDermott said, “Together, we have a great chance to shape the future, and incrementalism won’t do it. It’s time for change — to put AI to work for you.” ​

I’m currently working with the research team to update the research methodology with all the latest advancements in AI and how businesses are, and aren’t, transforming. Results due out in 2026!

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What Would AI Do? Rethinking Transformation from Procurement to the Enterprise at DPW

Live from the floor of DPW in New York, I had the privilege of joining my long-time friend Mark Perera on the DPW podcast. We explored the future of technology, business, and leadership, while also looking back to our roots in Silicon Valley during the rise of Web 1.0, Web 2.0, Social Media, and smartphones.

What made it truly special wasn’t just the set, it was the conversations I had with procurement leaders, innovators, and partners before stepping up to speak on behalf of ServiceNow. Listening to their challenges, their questions, and even what they hadn’t yet thought about, fueled what I brought to the stage and the podcast, and beyond.

I’ve studied disruption and transformation in Silicon Valley and its impact around the world for a long time. Again and again, I’ve seen the same pattern: new technology arrives, and companies use it to optimize what they already do, just faster, cheaper, more efficient moving forward. That’s necessary, but it’s not transformative. And these times are in need of transformative strategies.

Please excuse the plug, but it’s honest in its intent. My latest book, Mindshift: Transform Leadership, Drive Innovation, and Reshape the Future,is about breaking that cycle. It’s about giving ourselves permission to think differently, anticipating change and what comes next before disruption forces our hand. More so, it shows how to do things differently.

The Shift: From What We Did to What Would AI Do? – #WWAID

Throughout history, businesses have applied every major wave of technology to optimize the past. We make existing processes faster, more efficient, less expensive, more scalable. That’s progress and it is valuable. At the same time, it can also hold us to iteration, aiming to do what we did yesterday better tomorrow.

AI, however, invites a different question: What if the goal isn’t just to improve yesterday’s processes, but to invent tomorrow’s possibilities?

That’s where I ask WWAID, or What Would AI Do?

It’s a mental framework I use to break free from my own biases, expertise, and assumptions. Instead of asking “what would I do with AI?,” a question tethered to my perceived worldview, I try to explore the unknown for growth, and ask, “what would AI do in this moment?”

This subtle shift changes everything.

For example, in the case of DPW, we could ask (but it’s easy to adapt the questions to any industry or space):

Instead of: How do we make procurement 10% faster?Ask: What would procurement look like if it was designed natively with AI at the core?Instead of: How do we reduce costs in supply chain management?Ask: What if AI could redesign the supply chain itself to deliver on customer promises, sustainability goals, or brand values—not just cost savings?Instead of: How do we train employees to use AI tools?Ask: How can humans and AI collaborate as partners, each amplifying the other’s strengths, to create outcomes that neither could deliver alone?Beyond the 10%: Unlocking Exponential Value

Many organizations are focused on incremental gains, “the 10% mindset.” They implement AI in pockets, see some efficiency, and check the box. But the real opportunity lies in connecting workflows across silos. We could also call this group, “the 95% crew” if you read the recent MIT reportthat purported that 95% of generative AI pilots fail. As I shared in a recent analysis of that study, if you want bigger and better outcomes, you have to be bolder and more imaginative than in the past.

If you do what you’ve always done, how can you expect different outcomes. Yet, we do.

McKinsey’s QuantumBlack recently studied an array of generative AI use cases and found the highest returns didn’t come from isolated projects. Out of 25 attributes tested for organizations of all sizes, the redesign of workflows had the biggest effect to see EBIT impact. Said another way, instead of AI making one function better, it made the entire enterprise smarter and more profitable.

For procurement, that means moving from being a cost optimizer to being a strategic value creator. But I guess this is true for every industry and function. Imagine AI not just automating sourcing steps, but orchestrating how procurement ties into supply chain, product development, sustainability, and customer experience. Again, this is true as you reimagine work and workflows. This is no longer incremental improvement, it’s now about unlocking business model reinvention.

Escaping the Iterative Mindset

One of the biggest barriers to innovation is psychological. Even when leaders are asked to “think outside the box,” they bring their own industry box with them. Any brainstorm is still constrained by prevailing biases and assumptions, just dressed up with new buzzwords.

To truly innovate, we need to temporarily suspend expertise. Look at the most innovative companies outside your industry. Study their culture, their organizational design, their use of AI. Ask: What lessons can we borrow? And ask, what are they not doing?

When you shift your frame of reference, you stop seeing AI as just another tool for efficiency. It suddenly becomes an ‘AI status quo.’ You start to see it as an invitation to reimagine what your function could become in service of growth, customer value, and future relevance.

Platforms, Agents, and the Future of Work

At ServiceNow, we think of ourselves as the platform for AI-powered business transformation. AI by itself doesn’t transform businesses, it needs a foundation. And that foundation is rooted in mindset.

The future is agent-driven. Imagine workflows where the interface is the agent, where AI agents roam across siloed systems, pull in data, orchestrate processes, and deliver business outcomes without a human clicking through screens. In the process, they’re also learning, improving, and scaling in ways traditional IT stacks never could.

For leaders, this requires a mindset shift: stop reinforcing legacy processes with new tech. Instead, design workflows and strategies for the AI economy, a world where scale, speed, and creativity are no longer bound by headcount or historical silos.

My Personal Mindshift

I live these conversations every day with companies all around the world. I experiment with wearables like the Limitless Pin, which records and structures conversations into small language models I can query later, and then connects to larger models for insight. I use Meta’s AI glasses not just as hardware, but as an extension of my capacity in the real world and also cognition, translating languages in real time, narrating historical context as I walk through cities, and augmenting my curiosity in ways I couldn’t before.

Each of these experiments challenges me to think differently. They remind me that AI doesn’t have to replace us, with vision, it can extend us. The outcomes are efficiency gains and they’re entirely new ways of living, working, and creating. But that’s up to you. Start by asking WWAID?

A Call to Leaders

This is the moment for leaders to stop chasing incremental optimization and start defining what’s possible in an AI-driven future. Ask what would AI do if it were designing my function, my business, my industry from scratch? #WWAID

That’s where transformation begins. That’s where disruption becomes opportunity. And that’s the mindshift every leader needs to embrace.

—

Please listen to my full conversation with DPW to hear these ideas explored in depth, and to start asking yourself: What would AI do? #WWAID

Please watch my keynote at DPW NY.

Mindshift | Speaking | Newsletter

 

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Brian Solis to Explore How CEOs Should Navigate AI To Build the Organization of the Future, Today

Brian Solis is beyond excited to represent ServiceNow on stage at the prestigious Global Peter Drucker Forum.

The theme for this year is, “Leadership: All Hands on Deck.” It’s indeed the moment to retire the “business as usual” playbook and start thinking AI-Forward.

He will participate in an exclusive conversation with Johan Roos to explore the new C-Suite and the future of leadership.

Please join him and an entire cast of some of the most innovative, academic, and creative thinkers!

Program DescriptionThe CEO Guide to Using AI

How can senior executives capitalize on emerging AI tools to do their own work better? And how necessary will that become to their effectiveness and abilities to lead?

Chair
Johan Roos Executive Director, Vienna Center for Management Innovation (VCMI); Presidential Advisor Hult Int. Business School

in conversation with
Brian Solis Head of Global Innovation at ServiceNow; Futurist and Digital Anthropologist

Please visit the event site here to learn more and register.

 

 

 

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Brian Solis to Present at MetLife’s Triangle TechX (TTX) Event

Metlife just announced that Brian Solis will present on AI business model innovation at Triangle TechX (TTX).

The theme for this year’s event is “Agility Unleashed: Embracing STEM Innovation at Light Speed.”

Registration is free! Please sign-up here. Live and virtual opportunities are available!

 

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Hunter S. Thompson’s Lesson for Executives Determined to Automate Their Workforce

I was thinking about the Accenture and Walmart news on AI and jobs. It reminded me of a letter Hunter S. Thompson wrote a friend reminding him the importance of purpose in our work.

For power users, people are starting to “sound” like AI IRL and studies find that we’re losing our creativity and critical thinking the more we transfer brain power to gen AI.

We must have purpose in AI transformation and how we work with AI and agents. We cannot lose sight of human potential as we automate work. We must not lose the human in how we design work toward outcomes. We must make the outcomes, meaningful, to the business, and the recipients and beneficiaries of those outcomes. Otherwise, our work and unique value starts to become the next em dash.

“…we must make the goal conform to the individual, rather than make the individual conform to the goal. In every man, heredity and environment have combined to produce a creature of certain abilities and desires— including a deeply ingrained need to function in such a way that his life will be MEANINGFUL. A man has to BE something; he has to matter.”

There is something to be said about those who minimize work and those that maximize outputs and experiences to the beneficiaries of them. This video is a barometer for executives to decide on which side of transformation they want to be measured.

As humans, we sometimes, may too often, like to hit the easy button. But it’s short term gains over long term viability. We compete for the moment and not the future. Ironically, our fate isn’t just in the hands of AI and how leaders see the future of an AI workforce, but also how we shape our own destinies. Research already shows that we may already offload too much of our thinking and communication skills to AI vs. collaborating with it to do what was previously impossible.

In 2022, Airbnb was considering massive layoffs due to a sharp drop in bookings. Serving as a personal mentor to CEO Brian Chesky, Apple’s Jony Ive shared a long-term perspective as he weighed the cuts.

“You aren’t going to cut your way to innovation,” he told Chesky.

The same is true with AI business transformation.

In the end, you can’t automate your way to innovation.

If all you do is aim to scale what you did yesterday, you miss the opportunity for people and AI to collaborate toward achieving what was impossible yesterday, unlocking net new value creation and growth. The smart move is to balance both paths.

 

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Igniting AI Transformation: How to Future-Proof Your Company in the Age of AI

Technology moves at its own pace, adoption moves at the pace of culture. 

I joined Deloitte’s AI Ignition podcast with Beena Ammanath, Executive Director, Deloitte Global AI Institute, to talk about why AI feels different from past waves of technology, what it asks of leaders, and how we can turn disruption into a competitive advantage.

Beena opened by reminding us of a simple truth from Deloitte’s research: “technology moves at its own pace, but the adoption of the technology in an organization moves at the pace of the organization’s culture.” That became the backbone of our conversation.

Please watch/listen here .

Why AI Feels Different (and What to Do About It)

AI triggers something deeper than the usual automation cycle.

After watching the “Godfather of AI” Geoffrey Hinton’s sobering exchange with Steve Bartlett on Diary of a CEO about the future of jobs and humanity, I had to pause and think about our next steps. His vision for the future of work wasn’t, let’s just say, cheerful or terribly motivating. But fear without agency is paralyzing. It’s easy to spiral into dystopia. I believe the better move, however, is to treat those scenarios as inputs for planning, to reverse engineer those potential scenarios to help people take steps to reshape their future and the future of work, now.

Leaders and employees are still figuring out how to collaborate with AI. Most organizations are trying small automations or pilots, but “very few are reimagining what their future organization… can look like in partnership with artificial intelligence.”

That’s the work. We can shape what comes next.

I accept that there’s a lot to learn and a whole lot to unlearn moving forward.

Transformation begins with a mindshift.

To have that mindshift is to give yourself the gift of learning and unlearning, to see what you couldn’t see before, to do what you couldn’t do before.

We are all tempted to manage the future with the logic of the past. That only produces iteration. AI deserves, and requires, innovation, the pursuit of creating new value.

Beena underscored the same point from Deloitte’s research: technology moves at its own pace, but adoption moves at the pace of culture and change. If we do not evolve how we think and work, the technology cannot deliver its promise.

Begin with a Motivational Future State

Before roadmaps, start with vision. I shared how storied entrepreneur and venture capitalist Vinod Khosla’s provocation, “there’s only 200 people in the world that understand what’s really happening right now,” pushed me to go deeper.

Your job is to make that 201 inside your own company.

Start by defining a motivational future state: an inclusive and inspiring vision where you want to be in 18–24 months with AI and how you’ll know you’re on track along the way. The goal is to make that vision tangible and aspirational, one where people see themselves in it and believe they play a role in bringing that vision to life. Then reverse-engineer the steps and the measures (OKRs/KPIs) people can align to, and get to work.

This demands a mindshift:

“To transform your thinking and your organization, you have to start by disrupting yourself.”

It means unlearning patterns that default to incrementalism. Otherwise we “limit our opportunities and our outcomes to iteration and not innovation.”

Culture Is the Catalyst

I’ve spent years in transformation work. After studying waves of innovation, digital transformation and now AI business transformation, consistently, I found that the biggest catalyst andinhibitor in driving change is culture. Beyond vision and mission statements, behind earnings calls and publicity, people need to see themselves in the story and as part of story from beginning to end. They have to believe they have agency in the outcome, and share a vision, incentives, and motivation, with leaders and teams across the organization.

“If you can’t articulate what the future looks like… then you can’t have a culture that brings that AI transformation to life.”

Measure What Matters

Execution turns vision into velocity.

Beena pressed on execution. My answer: break the portfolio into three lanes in parallel, not sequentially. This was inspired by Gartner research:

Quick Wins to build confidence and momentum.Differentiated Use Cases that create advantages (not just an “AI-powered status quo”).Transformational Bets that alter trajectory.

If you can’t describe the vision and measures for each lane, you’re not ready to execute.

The Workforce: From Roles to Outcomes

Anxiety persists because people don’t see where they fit. So we cannot leave the workforce behind.

Build on the vision, then audit your workforce against your articulated future motivating state: which capabilities are missing, where do you excel, what can AI agents do today and tomorrow, what requires human orchestration, and how success will be measured?

Don’t tell people to “use AI for deeper work” without defining what deeper work is, how to get the skills, and how it will be recognized.

“What we can do is start to get some tangible elements…then look at the workforce and audit it…what are the jobs we need, what are the skills we need, how are we going to get people there, and how are we going to balance them with AI and train them to be able to execute?”

Fear and uncertainty recede when people know what success looks like and how they will be supported to get there.

Align Progress Against an AI Maturity Index

We also discussed industry patterns. From our latest ServiceNow AI Index, we saw AI maturity regress year over year by nine points. This was a huge finding in that, on average, companies scored 35 out of a possible 100 (with 100 being the most mature). Last year, the average score was 44.

We learned that this year, companies expressed that AI was moving too fast. In just the last three years, we’ve experienced the overnight rise of generative AI, then AI agents, and now the agentic enterprise. Organizations struggle with the speed of change and the governance necessary to safely and effectively pilot and scale.

Even so, I’m seeing bold pilots in manufacturing (robotics, computer vision, and physical AI); Beena noted strong acceleration in financial services and life sciences/healthcare, aided by rich data and maturing use cases.

The pattern is clear: governance plus vision plus experimentation accelerates maturity.

Dream bigger than optimization

Optimization is table stakes.

Short term, expect a lot of iteration… automation… optimization. And that’s good. It’ important to show how to improve what we did yesterday, better, less expensive, more scalable, tomorrow. That’s how enterprises adopt technology. Necessary, but not sufficient at the speed and scale we’re observing among AI-Native and AI-First companies.

The real opportunity is that AI offers the opportunity to do what you didn’t do yesterday. I foresee org charts where we see AI roles alongside employees and digital teammates. Done right, that yields not only linear growth but also exponential outcomes.

Using AI to rethink customer relationships

One practical example is CRM.

A practical opportunity: the “own” side of customer relationships. So many companies invest in acquisition motions and supporting infrastructure, but treat retention as a scrutinized line item…that is until customers threaten to walk away. But the own side is where value compounds.

“It’s less expensive and more strategic to keep a customer happy than it is to try to acquire a new customer.”

AI can change that. We’ve long treated service and success as cost centers. But no one wakes up hoping to talk to a chatbot or sit in a contact-center queue. With AI agents dedicated to customers, we can deliver real outcomes fast, reduce complexity, and convert service into growth.

AI can turn service and success from cost centers into growth engines, with agents dedicated to customers, integrated journeys, and outcomes that feel as valued as the day they signed.

Closing: Choose to Be the Company Others Follow

This is your moment to decide whether AI happens to your organization or throughit. The difference is a leader willing to say, “I don’t know what I don’t know,” and then act with conviction to fill in the blanks.

Here’s my challenge to you, wherever you are in the organization, a 90-day sprint to make the future tangible:

Week 1: Leaders, write your one-page motivational future state. Invite input. Name the customer and employee outcomes they will feel in 12–18 months. Share it with your leadership team.

Week 2–3: Stand up an AI Governance & Value Office that pairs risk with product, ops, and finance. Set non-negotiable metrics for adoption, experience, velocity, and revenue impact.

Week 4–6: Launch your three-lane portfolio: 3 quick wins (confidence and capacity), 2 differentiated use cases (what your peers aren’t doing), and 1 transformational bet (what changes your trajectory).

Week 7–8: Audit roles and skills against the vision. Publish a mindful human + agent org chart that empowers and augments your workforce, not automate them out. Fund learning paths tied to recognition and rewards. Document your potential for exponential output not possible otherwise. This is your future moat.

Week 9–10: Reinvent the “own” side of your business with CRM, shifting from a cost-center mindset to an infinite growth center. Pick one critical customer journey and deploy agents to deliver end-to-end personalized experiences and outcomes customers would choose again.

Week 11–12: Hold an Unlearning Review. Retire one legacy KPI, one legacy process, and one legacy belief that no longer serves the vision. Celebrate what you moved from iteration to innovation.

Put dates on a calendar. Name owners. Allocate budget. Report progress to your board monthly. You’ll discover that once the vision is explicit and measured, momentum compounds. Put words to it, articulate learnings and a future-motivating state, and culture follows.

Obviously this is fast, too fast for most to willingly embrace. So what? We don’t need to wait for perfect timelines or clarity to lead. We need the courage to begin, the discipline to measure, and the humility to learn and unlearn along the way…especially in the face of the unknown. I

Define what happens next.

If you take this 90-day challenge, tell me what you learned and what you built, or at least, did differently.. Let’s make this the year we chose transformation over hesitation and formulaic automation, to become the companies others follow.

AIdapt or Die!

Mindshift | Speaking | Newsletter

 

 

 

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Brian Solis Selected as Featured Speaker at SXSW Sydney 2025

Brian Solis is excited to announce that he’s joining SXSW Sydney 14 October.

His session: “AI as the Mindshift for a New Leadership Paradigm” is open to all who welcome the opportunity to explore how AI unlocks new paths forward.

Please add his session to your agenda.

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Brian Solis Joins Be Customer Led Podcast to Reimagine Customer Experience in the Age of AI

In this episode, we welcome Brian Solis, Head of Global Innovation at ServiceNow, a nine-time best-selling author, keynote speaker, and digital futurist. Starting the conversation, Brian shares the inspiration behind his latest book, “Mindshift”, and emphasizes the importance of empathy and a truly customer-centric mindset.

Through examples from Amazon, Disney, and IKEA, Brian illustrates how organizations can create meaningful and memorable experiences that drive both loyalty and growth.

The conversation also explores the evolving role of AI, shifting from automation and cost savings to augmenting human interactions and delivering personalization. Finally, Brian calls on leaders to embrace innovation, cultivate empathy, and invest in customer experience as a catalyst for transformation and long-term success!

Listen on Apple Podcasts

[00:31] Guest Introduction[02:00] The Concept behind “Mindshift”[04:07] Empathy and Customer-Centric Approach[13:30] The Role of AI in Customer Experience[26:34] Developing Leadership Skills for Customer Experience[31:25] The Future of AI in Customer and Employee ExperienceResources:

Connect with Brian:

Website: briansolis.com/

LinkedIn: linkedin.com/in/briansolis

Mentioned in the episode:

Mindshift: Transform Leadership, Drive Innovation, and Reshape the Future: amazon.com/Mindshift-Embracing-Unlimited-Possibilities-Visionary

Blueprint for Customer Obsession: amazon.com/Blueprint-Customer-Obsession-Marbue-Brown

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