Artificial intelligence is constantly in the news, and it’s one of the most talked about topics among our Fast Company Impact Council members. Its use and acceptance levels are changing daily, with company direction on how to approach it changing alongside that. Boards, leadership, teams, and customers are also reassessing AI usage in the workplace and in the work product. We asked our Impact Council members what kinds of attitude changes toward AI they are seeing in their ecosystem. This question drew an onslaught of replies—clearly a topic everyone has thoughts about. We are sharing 26 of their responses, ranging from the theoretical to unusual use cases.
1. MOVE AWAY FROM GENERIC USES
There’s a divide in how leaders are using it in their communications with teams and the public. There’s a group that is being more passively led by the capability, writing generic content which doesn’t actually sound like them, full of “it’s not this, it’s that,” and dramatic three-word sentences. Arguably it’s doing more harm than good for them. And then there’s a smaller group that is investing time in it to make the LLMs an extension of themselves, using it for their passions, creating custom GPTs, vibe coding useful web apps, training it how to write like them. And you can see them scaling their impact in a really cool way. — Neil Barrie, TwentyFirstCenturyBrand
2. FROM INVESTMENT TO OPERATIONALIZATION
Across the board, we’re seeing a shift from what AI investments you’ve made to how AI is operationalized, into process and workflows. Grand pronouncements about AI are meaningless if the benefits aren’t made tangible. For our teams, that translates to a shift from general AI training sessions to functional, role-based sharing of use cases and how AI can streamline work, save time, and drive efficiency, in practice versus theory. We’re also seeing a surprising dichotomy, especially in our younger staff, between those who fully embrace AI and those who are skeptical, if not resistant to AI based on its ethical and environmental impact. — Celia Jones, FINN Partners
3. AI’S IMPACT IS DRIVING URGENCY
There has been a clear shift in attitude toward AI across the board, especially among our customers. While education has traditionally adopted new technologies with caution, the profound impact AI is already having on the workforce is driving urgency. That urgency is accelerating experimentation, but it’s also raising the bar. Educators and institutions are no longer just exploring what AI can do. They are now asking how it can be applied in ways that meaningfully solve real challenges and drive improved learning outcomes. — Darren Person, Cengage
4. IT’S NOW EXPECTED, NOT EXPERIMENTAL
The conversation around AI has flipped. It’s no longer experimental, it’s expected. Boards and customers aren’t asking “if,” they’re asking, “where’s the impact?” Internally, our team members are moving faster than expected past the fear narrative to curiosity and adoption. — Steve Holdridge, Dayforce
5. IMPACTS TO GOVERNANCE
Governance leaders are shifting their focus from “How do we slow this down?” to “How do we move faster without losing control?” Because when governance doesn’t keep pace with AI’s speed and scale, the risk is both operational and existential. Businesses don’t just risk AI projects going live without proper guardrails—and the compliance and trust issues that follow. They also risk stalling innovation and losing ground to competitors. This reality is reshaping the mindset around AI governance, where speed is no longer a nice-to-have but a fundamental requirement. — Blake Brannon, OneTrust
6. GROWING USAGE
Attitudes toward AI are shifting quickly. AI’s potential is strong, and it’s increasingly being used in the workplace. This usage is exposing where major faults still lie, understandably leading to hesitation to adopt. Today, most of the use is for individual or team productivity, but it’s expanding. As the technology improves, I anticipate AI will extend through many business functions, especially regarding repeatable tasks and processing large amounts of data. We’re already seeing companies and educational institutions establish organizational hierarchies to perform work with AI agents alone, underscoring the pace of adoption. — Andrea Montecchi, Oliver Wight
7. HOW FAST CAN IT SCALE?
The shift is clear: AI has moved from “Why?” to “How fast can we scale it?” In our global design practice, it’s no longer experimental—it’s embedded in everyday workflows from research to concepting to decision-making. The smartest leaders start with one high-impact use case, prove value quickly, and expand from there. The competitive edge now belongs to organizations that treat AI as a core capability, not a future bet. — Susan Watts, SPACECRAFT LLC
8. MEANINGFUL COMPANY DIFFERENTIATOR
From my perspective as a CMO, attitudes toward AI—both internally and with stakeholders—have shifted dramatically in a very short time. AI is no longer viewed as a supporting tool, but as a core leadership capability and meaningful company differentiator. Organizations that embrace AI recognize that its true value is strategic. While efficiency gains and faster time to impact matter, the greater advantage is AI’s ability to drive smarter decisions, competitive differentiation, and sustained growth—outweighing earlier concerns or hesitation. — Felicity Carson, onsemi
9. MISSION-CRITICAL AMBITION
In a few months, AI has gone from aspirational and experimental to a mission-critical ambition. Brands, humbled by early experiments and vendor overpromising, have tempered their expectations while the quality of the models has taken a real leap since late 2025. The result is a narrowing gap between AI expectations and reality. — Pierre-Loic Assayag, Traackr
10. AI AS PARTNER
Our teams are beginning to see the potential of AI, and slowly but surely warming up to the era of AI as a partner. The adoption, though, hinges on trust, performance, quality, and most importantly, output accuracy. It’s also clear that the competency to supervise, govern, and execute AI skills is critical for how each team member can leverage the most out of AI. — Arin Bhowmick, SAP
11. HOW TO MEASURE WHAT’S WORKING
I’ve been working with AI since the 1990s at NASA, applying neural networks to space shuttle simulations and robotic brain surgery, so I have a long frame of reference. Being an early adopter matters and we leaned into AI at Age of Learning before it was mainstream. This gave our teams the comfort and fluency to move fast when the technology took off. Today almost 90% of our code is created by engineers with AI support, and our board has shifted from “What’s our AI strategy?” to “How do we measure and scale what’s working?” That’s the right question for any leadership team to be asking right now. — Alex Galvagni, Age of Learning
12. FROM UNCERTAINTY TO INTENTION
The tone has shifted from uncertainty to intention. People are moving past the question of whether AI matters and focusing on how to use it responsibly and safely. In my industry, they’re finding ways that create value for students and educators. We use AI to help educators build confidence using it in the classroom. We partner with industry to provide the comprehensive support schools need as this technology reshapes learning and work. AI in education is not just about exposure to a tool. It is about preparing students to think critically, innovate, collaborate, and lead in a world where AI will touch every industry. — Kellie Lauth, MindSpark
13. PRODUCTION INFRASTRUCTURE
The big shift is from AI as a side experiment to AI as production infrastructure. A year ago, teams were trying a few tools in the corner; now AI is baked into real workflows across engineering, support, and ops. Security teams are playing catch-up, not because they were asleep at the wheel, but because the volume and variety of tools exploded all at once. The new question isn’t whether to use AI; it’s how to get visibility and control over what’s already in use without slowing everyone down. — Avery Pennarun, Tailscale
14. FROM CURIOSITY TO EXPECTATION
There’s been a clear shift from curiosity to expectation. AI is no longer a side conversation; it’s embedded in how we prototype, iterate, and scale ideas through proprietary platforms and our broader innovation ecosystem. But we’re disciplined about it. AI is only as powerful as the humans directing it, and we see it as a multiplier of creative thinking, not a replacement for it. The real unlock is pairing the speed of AI with the judgment, taste, and ambition of the right creative and strategic leaders. — Emily Wilcox, TBWAChiatDay NY
15. IT’S BECOMING TABLE STAKES
There’s been a clear shift. AI is no longer a differentiator, it’s becoming table stakes. Our customers aren’t asking if we use it; they expect it to drive transparency, speed, and smarter decisions across the supply chain. The real risk is adopting AI without discipline. As we build AI fluency, we have to stay human-led and monitor how model performance influences overall impact. Judgment, context, and accountability increasingly matter. The advantage will come from using AI better than everyone else. — Clare Woodford, Alpine Group—Paradise Textiles and Alpine Creations
16. CREATES VALUE WHEN GROUNDED IN DATA
The conversation is maturing fast. The expectations have always been high; the question has been of readiness. Boards, customers, and teams all want to see AI working at the last mile, within real processes, producing real outcomes. “Just add AI” is where AI goes to die. There’s growing excitement, but it’s paired with pragmatism and a clear understanding that AI only creates value when it’s grounded in data, embedded in workflows, and owned by people who know the work. — Balkrishan “BK” Kalra, Genpact
17. HOW FAST TO ADOPT?
AI is no longer a discussion about the future. It has become a conversation about who will be left behind. Ramping up adoption within the company and the industry is no longer theoretical, it is a mandate. Even six months ago, conversations around AI were still around whether to adopt it. Now it’s simply where, how fast, and what can it unlock. What is possible now has completely leveled the playing field for time and cost to build technology. — Regan Parker, ShiftKey
18. JOB CANDIDATES CARE
From a talent perspective, AI has gone from a “nice to have” to a baseline expectation. Candidates are actively evaluating how organizations are integrating AI into their internal operations, and if a company isn’t leaning in, it raises bigger questions about its approach to innovation. It’s a signal of mindset, agility, and future readiness. — Meredith Rosenberg, NU Advisory Partners
19. MORE REFINED POSITION ON AI
One of the biggest shifts I’ve seen, both within our teams and in how we counsel clients, is a more refined AI position: AI-powered, human-led. It’s how you build trust in this era of AI slop. In the early days, generative AI was seen as a shortcut to content production, but we’ve learned that a thousand nearly identical, obviously AI-generated posts drive content value to zero. Now, the goal is to lead with human experience and creative dot-connecting, with AI supporting the work, helping to edit, refine, or ensure tonal alignment. — Tyler Perry, Mission North
20. AI FEELS INEVITABLE
There is absolutely a shift in attitude toward AI at both the board and team level. What felt experimental now feels inevitable. Teams are adopting AI through gateway use cases like search, drafting emails, summarizing materials, and note taking. These are building confidence and encouraging further experimentation. At the board level, the conversation has moved from curiosity to accountability, with a focus on ROI, risk, and governance. The real shift is from efficiency to redesigning work. The real risk right now is treating it as a side tool instead of a core business transformation. — Tami Rosen, executive and board member
21. A LEADERSHIP IMPERATIVE
AI is now prompting much deeper conversations about the workforce and about whether people are truly prepared for what is changing around them. Leaders are asking harder questions about how roles are evolving, what skills talent needs to bring, and how quickly their own teams and customers need to build new capabilities. The most important shift is the recognition that AI is no longer a tool to experiment with, but a leadership imperative about making sure people can use it thoughtfully, apply it responsibly, and understand where human judgment and accountability still need to lead. — Justina Nixon-Saintil, IBM
22. A BASELINE TOOL
There’s a clear shift from curiosity to expectation, but then with a layer of guilt and uneasiness. At first, when work product was clearly AI-generated, it was dismissed. Now if it’s clear AI was not used, it raises red flags. There must be balance, wording that is clearly in your voice, and consistency and understanding. Our team and partners see AI as a baseline tool, not an experiment, especially for research, iteration, and communication. But in the end, decision-making must be human. Customers don’t ask about AI directly, but they feel the speed and clarity it enables. — Ben Wintner, Michael Graves Design
23. NEEDS EVALUATION
The technological landscape is evolving rapidly, and companies today either choose to adapt and lead, or remain stagnant and fall behind. Partners, customers, and stakeholders expect smarter, faster, and more transparent operations. Because of this, AI is a tool that needs evaluation to determine if it can help meet those demands while driving measurable value and as a lever for operational efficiency and competitive advantages. At the same time, this technology comes with responsibility. As we integrate AI into businesses, we need to maintain strong safeguards around data and how we activate these innovations within our operations. — David Klanecky, Cirba Solutions
24. IT BOOSTS INCLUSION
We embraced practical AI use early—for productivity, organization, and as a creative thinking sparring partner. We’ve seen growing adoption and positive feedback from within our org and users on our AI chatbot, which accurately answers questions about neurodivergence. With a third of our team identifying as neurodivergent, we’re also interested in AI’s impact on this community. Our recent survey suggests AI is empowering neurodivergent employees, with over half saying it’s increased their confidence applying for higher-level roles they’d avoided. When used to support people—not replace them—AI can boost productivity and inclusion. — Nathan Friedman, Understood.org
25. PEOPLE DEPEND ON IT DAILY
The attitude shift around AI is profound. Consumers aren’t just adopting AI, they expect it to understand their lives. A year ago, people were experimenting with AI; now they depend on it every day. As comfort grows with the technology, expectations become greater. We’re seeing a rising demand for ambient AI, that reads the room and acts. No one wants to prompt their way through life in the long term. We’re focused on shaping AI as an infrastructure that disappears into the background and integrates across devices and systems. We want to build technology that delivers on “what’s missing” before the consumer even needs to ask. — Yoonie Joung, Samsung Electronics America
26. START FROM THE MARGINS
With AI evolving rapidly, attitudes can’t stay static. We believe in building with communities, not for them. The most effective AI adopters start from the margins rather than the technology. Our Solvers—entrepreneurs tackling global challenges—use AI to compress timelines that once took a decade. LifeBank in Nigeria uses AI-driven logistics to reach 3,000 hospitals and 40 million people; SXD applies AI to zero-waste design, cutting CO₂ emissions by 80%. Urgency and scarcity can drive more thoughtful, human-centered AI than I see elsewhere. — Hala Hanna, MIT Solve
