Will Your Company Culture Shape Your Company’s AI — Or Will AI Shape Your Company’s Culture?

By Joshua Hollander

In boardrooms across the middle market, a quiet power struggle is unfolding: the ethos of a company versus the algorithms it employs. It’s no longer science fiction – it’s a strategic reality every CEO must confront. The core question is provocative: Will your company culture shape your company’s AI, or will AI shape your company’s culture? With 78% of midsized companies already using AI in some form, this isn’t a hypothetical debate. How you answer it could determine your organization’s future.

Let’s explore both sides of this dilemma – and then chart a path for leaders to turn this tension into a competitive advantage.

Culture Shapes AI: When Values Drive Technology

Company culture has long been the invisible hand guiding “how things get done” internally. In the age of AI, culture can dictate how technology is adopted, applied, and even whether it succeeds or fails. As management guru Peter Drucker might have warned, culture eats AI strategy for breakfast. Even the best AI plans falter without the right cultural foundation.

Consider how a strong, purpose-driven culture steers AI use: leaders at companies with clear values tend to align AI projects with what matters most to their organization. Gallup observes that organizations should invest in AI that reinforces their purpose and competitive differentiation – for example, if your culture prides itself on exceptional customer service, deploy AI to enhance service, not replace it. In other words, let your values dictate where and how AI is used.

Real-world case studies bear this out. Stitch Fix, an apparel retailer, built its brand on personalized styling. Even as AI dominates retail headlines, Stitch Fix recently rebooted its customer experience by doubling down on human stylists. Its algorithms still crunch data behind the scenes, but the company’s culture of personalization meant AI is used as a tool for the human stylists, not a replacement. The lesson: a company with a clear cultural mandate (in this case, human-centered service) will bend even cutting-edge AI to uphold that mandate.

Culture also determines organizational appetite for AI. In some firms, employees and even executives are culturally biased toward “gut feel” decision-making. One study found 67% of C-suite executives were “not comfortable” relying on AI analytics, preferring intuition instead. That cultural skepticism can stymie AI initiatives. On the flip side, companies that celebrate data-driven decisions and continuous learning create an environment where AI thrives. As one Deloitte report noted, data-fluent cultures encourage teams to question outputs and test ideas, rather than blindly trust a model. Wayfair, for instance, nurtures a “culture of experimental validation” – no one can say “the model told me so” without evidence; every AI insight is scrutinized and tested. This cultural norm ensures AI augments human creativity instead of overruling it, and it gives people confidence to work with AI critically.

In short, your culture — the shared values, behaviors, and norms in your business — will heavily influence which AI solutions you pursue, how you implement them, and how your people interact with them. A trust-filled, innovative culture will push AI use in positive, value-aligned ways. A fearful or unclear culture may reject AI or misuse it. As Reece Akhtar, CEO of a culture analytics firm, pointed out: “In a future where access to AI is democratized, an organization’s culture is not just an asset; it’s the only moat.” In other words, when every company has AI, your culture becomes your competitive edge in how you wield it.

AI Shapes Culture: Technology as a Transformative Force

The influence runs both ways. Introduce a powerful new technology into an organization, and you will inevitably change the organization. AI is no exception – from the C-suite to the frontline, it is already reshaping company cultures, for better and for worse.

On the positive side, AI can be a catalyst for cultural evolution toward agility, innovation and learning. Companies that embrace AI often see a mindset shift: teams become more adaptable and curious as they incorporate new tools into daily work. A joint MIT Sloan/BCG report found that AI’s introduction is often accompanied by a more growth-oriented culture focused on innovation and continuous learning. When routine tasks are automated, employees have more freedom to focus on creative, strategic work, which can boost morale and a sense of purpose. Mundane drudgery fades, making space for upskilling and more meaningful contributions. Over time, this shapes a culture that values higher-level thinking and development. In essence, AI can raise the bar for what “work” means in your company – turning your workforce into learners and problem-solvers rather than button-pushers.

However, AI’s impact on culture can also manifest as disruption and anxiety if not carefully managed. Imagine a company introducing an AI system that monitors employee performance or makes hiring decisions. Without the right context, this could sow fear or distrust. In fact, surveys show an overwhelming majority of employees are anxious about AI’s impact on their jobs – 75% fear AI will make certain jobs obsolete, and 65% worry their own role could be replaced. If leadership doesn’t address these fears, the culture can quickly turn defensive, with employees resisting new tools or quietly disengaging. We’ve seen high-profile examples of AI deployments backfiring due to cultural backlash – such as when an AI-driven scheduling tool led to anger over unpredictable work hours at a retailer, or when a big tech company’s attempt at AI-based hiring ran into employee concerns about bias. These incidents underscore that AI can erode trust and openness if it’s perceived as a threat or implemented in a vacuum.

Yet, proactive leaders are showing that AI can be used to strengthen culture when aligned with human needs. Veolia, a global services firm, faced a culture of silence around reporting problems. They deployed an AI-enabled anonymous reporting platform (Whispli) to empower employees to speak up. Management knew employees often spotted issues but feared repercussions for raising them. By using technology as a confidential channel, Veolia saw a surge in tips and greater inter-departmental trust – the AI tool actually helped reinforce a culture of integrity and transparency. In this case, AI shaped the culture for the better, because leadership applied it thoughtfully to address a human concern.

AI is also redefining organizational norms. When algorithms handle more decision-making, companies often shift to a culture that prizes data and outcomes over hierarchy and tradition. For example, at some firms, junior analysts armed with AI insights can challenge the opinions of veteran managers – changing the culture to be more meritocratic and evidence-based. Additionally, the rise of “digital co-workers” (bots, chatbots, RPA agents) means humans are learning to collaborate with non-human teammates, altering collaboration and workflows. John Sviokla, former PwC CMO, advises that companies must rethink roles and processes so that human and digital workers can amplify each other’s performance. This might mean a cultural shift where experimentation is encouraged at all levels, and cross-functional teams rally around AI projects in a way that breaks old silo mentality.

In sum, AI will inevitably leave its thumbprint on your company culture. It can push your organization to be faster, more innovative, and more data-driven – or it can introduce stress, ethical dilemmas, and fragmentation. The outcome depends largely on the intentionality of leadership in anticipating these shifts. Will you let AI drive without a human hand on the wheel, or will you steer the cultural changes it brings?

The Leadership Imperative: Aligning Culture and AI for Success

Rather than picking sides – culture versus AI – savvy leaders see this dynamic as a both/and proposition. Your culture should shape your AI use, and your AI will shape your culture. The goal is to create a virtuous cycle where each reinforces the other positively. Achieving this requires deliberate leadership. CEOs and boards of middle market companies must grapple with several key imperatives at this AI-culture crossroads:

Maintaining Organizational Viability: Above all, leaders have to keep the business viable amid rapid change. In today’s environment, ignoring AI is not an option – it’s as existential a risk as ignoring the internet in the 2000s. Adopting AI is now central to staying competitive and efficient. But how you adopt it matters for long-term viability. Push too hard in a way that clashes with your culture (e.g. automating customer service in a company known for human touch) and you could implode employee engagement or customer loyalty. The imperative is to embrace AI in a way that your organization can digest. This might mean pacing implementation with change management, and choosing AI projects that clearly enhance (not betray) your company’s mission. Remember that 85% of middle-market executives said generative AI’s impact was more positive than anticipated – the opportunity is real, but over half also said implementation has been harder than expected. Organizational resilience – the ability to adapt without breaking – will depend on respecting the cultural limits even as you push forward. In short, adopt AI to survive, but do it in a culturally mindful way.
Defining What Is Core (and Should Remain Human): Not everything your company does should be handed over to AI. A critical leadership task is to distinguish core competencies and values from commoditized activities. Core areas – often tied to your brand’s uniqueness or deep expertise – may warrant a human-led or human-plus-AI approach rather than full automation. For instance, if your core value proposition is creative design, you’ll use AI as a brainstorming partner for your designers, not as a replacement for their creative spark. On the other hand, contextual or support activities (like routine data processing, basic customer inquiries, etc.) might be ripe for AI automation or outsourcing, freeing your people to focus on what humans excel at. This boundary-setting is cultural: it tells your organization “these things define us, and we’ll use AI to enhance them – those other things, we’re comfortable letting technology or partners handle.” Leaders at Gallup call this “aligning AI investment with purpose” – ensuring you deploy AI in areas that amplify what makes your company you. Defining core vs. non-core also guides whether you insource or outsource AI capabilities. If building an AI solution in a core area will differentiate you competitively, consider insourcing it (e.g. developing proprietary AI in-house). If it’s a non-core function, you might safely outsource to an AI vendor or partner. Many midsize firms realize they need external help – 67% of middle market executives say they require outside assistance to get the most out of AI – but the key is to use partners for the right things. Don’t outsource your secret sauce.
Future Organizational Design: Embracing AI means redesigning the structure and roles within your organization. Leaders should envision what a future “human + digital” workforce looks like in their company. Which new roles are needed (e.g. data scientists, AI model trainers, AI ethicists)? Which existing roles will evolve (perhaps your analysts become “AI-augmented analysts” who can tackle 10x the data)? Will some departments shrink while others grow? Proactive CEOs are already creating AI task forces or centers of excellence to spread expertise internally. Importantly, consider how teams will be composed: you might have a bot sitting alongside humans in a workflow – for example, a human resource team that includes a machine-learning based résumé screening tool as one of its “team members.” The culture needs to shift to normalize this collaboration. This could mean updating your org chart and processes to explicitly assign certain tasks to digital workers and others to humans, and establishing protocols for escalation between them. Organizational design also extends to decision rights: if an AI can make a call on credit risk in seconds, what is the role of the credit manager now? Perhaps to handle exceptions and to train the AI on edge cases. Leaders must define these new interactions clearly so employees understand their place in an AI-enabled firm. Done right, this future design can make your company more agile and scalable; done haphazardly, it can create chaos. Design for clarity, collaboration, and continuous learning.
Balancing Human and Digital Workers: The workforce of the future will be a blend of humans and AI systems (your “digital employees”). Leaders need to actively manage this balance. Human talent is scarce and precious, and AI is powerful and scalable – how do you get the best out of both? A key imperative is to preserve and elevate the human element even as you automate. One CEO insightfully noted: as AI creates efficiency and financial gains, reinvest some of those gains into your people – through training, upskilling, even better pay – to create a positive feedback loop where human and digital workers amplify each other. History offers a lesson here: when Henry Ford introduced automation via the assembly line, he doubled workers’ wages, ensuring they remained motivated and could also afford his cars. Today’s leaders should similarly strengthen their human team even as AI does more heavy lifting. Culturally, you must send the message that AI is here to empower, not replace. Encourage employees to view AI as a colleague – one that handles the grunt work – so they can focus on higher-impact activities. Also, foster cross-training: teach your human workers enough about AI tools to work confidently with them (remember that nearly half of employees using AI say they’ve received no training on it – that gap breeds frustration). The companies that strike a healthy balance will enjoy a workforce that is both highly efficient and highly engaged.
Competitive Positioning: Middle market companies often worry (rightly) about being outflanked by larger rivals with deeper pockets for technology. But culture can be the great equalizer. If you intentionally shape a culture that’s nimble with AI, you can leapfrog competitors. Think of culture as the rocket fuel for AI adoption: a culture of innovation will implement and iterate AI solutions faster, a culture of customer-centricity will apply AI in ways that create standout experiences, etc. Also, as AI becomes ubiquitous, having AI will no longer be a differentiator – but having a strong culture will. As noted earlier, when everyone has access to similar algorithms, culture is “the only moat” that sets you apart. For example, two firms might use the same AI platform for supply chain optimization, but if one has a collaborative culture that breaks silos, it will execute changes from AI insights far better than a siloed competitor. Leaders should ask: what can we do with AI that our competitors can’t, because of who we are? Perhaps your culture of trust means you can share more data with partners, yielding better AI predictions in your supply chain. Or your culture of risk-taking lets you pilot an AI product faster in the market. Use cultural strengths to maximize AI, and conversely, use AI to extend those strengths – this synergy will define your competitive position in the AI era.
Insourcing vs. Outsourcing Decisions: Finally, a pragmatic imperative: deciding what AI capabilities to build in-house versus buy from outside. This is both a strategic and cultural decision. Insourcing (building your own AI team, developing proprietary algorithms) can give you tailored solutions and unique IP – aligning with a culture that values innovation and self-reliance. It can also foster an internal culture of experimentation (your people learn by doing). On the downside, it’s costly and requires scarce talent, which might strain a culture not accustomed to high-tech development. Outsourcing or partnering, by contrast, can get you up and running quickly using expert providers – aligning with a culture focused on efficiency and speed. However, relying heavily on external AI solutions might limit your internal learning and could clash with a culture that prides itself on owning its processes. Many middle market firms choose a hybrid “co-sourcing” approach: partner with AI vendors or consultants to jumpstart projects, while having internal staff shadow and learn, eventually bringing the capability inside. Whatever the mix, leadership should make the rationale clear. If you outsource, ensure the vendor understands your company’s values and way of working (so their solution fits your culture). If you insource, ensure your tech teams are integrated into the business and culture (not a silo of data scientists doing projects nobody understands). And revisit these decisions periodically – as your people become more AI-savvy, you might pivot from buying to building. The guiding principle: outsource commodity tech, insource strategic tech. If an AI system will directly shape your customer experience or core operations long-term, you want at least partial in-house control over it. In all cases, maintain oversight at the board level for ethical and performance considerations, regardless of who builds the tool.

By weighing these imperatives, CEOs and boards can navigate the interplay of culture and AI with intentionality. It’s a balancing act: staying adaptive and tech-forward (to remain viable and competitive), while fiercely protecting what is culturally sacred and human (to remain true to your purpose and people).

Key Questions for CEOs and Boards

As you steer your organization through this AI-cultural evolution, it’s useful to pose tough questions in the boardroom and C-suite. Here are some of the key questions leaders in middle market companies should be asking themselves:

“Are we crystal clear on what defines our culture and brand – and are we aligning our AI initiatives to reinforce those elements (rather than undermine them)?”
“What do we consider our core competencies, and how will AI help us do those better? Conversely, what activities should be automated or outsourced so we can double down on our core?”
“How might our organization’s structure and jobs need to change in the next 3-5 years because of AI? Do we have a plan for redesigning roles, retraining staff, and integrating ‘digital workers’ alongside humans?”
“What fears or resistance might our employees have about AI? Are we addressing those openly and providing training so that people feel prepared and optimistic about working with new technologies?”
“In what ways could AI adoption potentially erode our culture or values, and what guardrails do we need (ethical guidelines, policies, oversight mechanisms) to prevent that?”
“Is our culture agile enough to experiment and learn with AI – does it tolerate failures and encourage innovation, or do we need to cultivate a more experimental mindset among our team?”
“How do we measure success for AI initiatives beyond cost savings or efficiency? (e.g. impact on customer satisfaction, employee engagement, speed of innovation) – and do those metrics align with our strategic goals?”
“Regarding talent and technology: which AI capabilities must we own and build internally to stay competitive, and where should we partner or buy? Do we have the right mix of tech talent, and is our HR pipeline gearing up for an AI-skilled workforce?”
“Are our CEO and board actively engaged in understanding AI opportunities and risks? How can we increase our leadership’s AI fluency so we ask the right questions and set the right tone from the top?”

Pondering these questions is not a one-time exercise. They should become part of your strategic planning rhythm. By regularly assessing these facets, you ensure that you’re not sleepwalking into an AI deployment that drifts away from your company’s DNA. Instead, you’ll approach AI with eyes wide open and a deliberate plan.

From Insight to Action: How to Shape This Dynamic Intentionally

Provocative questions and high-level principles are only valuable if they lead to action. How can middle market CEOs and boards practically guide the relationship between company culture and AI? Here are clear, actionable steps to take:

Articulate a Vision where AI Amplifies Your Culture: Craft a compelling narrative about why and how your company will use AI, anchored in your mission and values. Communicate from the top that “We are adopting AI to further our purpose of X…”. For example, “We’re using AI in customer service to extend our hallmark hospitality, not to reduce it.” When employees hear that the AI strategy is a natural extension of what the company already stands for, they’ll be more bought in. Gallup found that employees are 2.9× more likely to feel prepared for AI when leadership communicates a clear plan. So be transparent about what will change and what won’t. Storytelling here is powerful – paint a picture of a future where your human team and AI together achieve goals that seemed out of reach before, all while staying true to who you are.
Invest in Skills and Mindsets, Not Just Technology: Middle market firms often operate with lean teams, so the temptation is to plug in a tool and hope for the best. Resist that. Budget for training programs to raise the data and AI literacy across your organization. This could include workshops, online courses, or bringing in experts to coach teams on new AI-driven processes. Remember, nearly half of workers say they haven’t been trained in how to use AI – don’t let your employees be part of that statistic. Also, cultivate the right mindsets: encourage curiosity and experimentation. You might implement an incentive for employees to suggest AI use cases or run small pilots. Celebrate those who try something new with AI (even if it doesn’t yield an immediate ROI) to signal that smart risk-taking is part of the culture. By developing your people, you turn them into willing partners in the AI journey rather than roadblocks. This step also involves talent decisions: if you lack certain expertise, decide whether to hire new talent, upskill existing employees, or partner externally – but ensure whoever is working on AI for you understands and fits your culture.
Start with Pilot Projects that Model the Future: Rather than a big-bang AI rollout, pick a few high-impact, manageable pilot projects. Choose areas where AI can solve a real pain point or create quick wins, and where the cultural stakes are not irreversibly high. For example, automate a tedious back-office process, or deploy an AI tool to assist (not replace) a team with heavy workloads. Make these pilots explicitly “learning projects” – the goal is not only the immediate benefit, but also to learn how AI integrates into your workflows and how your people adapt. Use cross-functional teams to run the pilots, mixing IT, business, and HR folks. This not only yields better technical outcomes, but also fosters a culture of collaboration around AI. When a pilot succeeds, publicize the story internally: “Look how our sales team worked with a new AI tool and boosted productivity 20%. Now they have more time to spend with clients – and they’re loving it.” Early case studies within your own company build momentum and positive cultural buzz. If a pilot fails or hits obstacles, be transparent about that too – and frame it as learning (e.g. “We discovered our data wasn’t as clean as we thought, which we’re now fixing”). This reinforces that failure is acceptable in pursuit of innovation, which is a hallmark of adaptive cultures.
Establish Guardrails: Ethics, Data Governance, and Role Clarity: To prevent AI from inadvertently corrupting your culture or causing harm, put guidelines and governance in place from the get-go. Develop a clear policy (or principles) on how your organization will use AI – covering issues like data privacy, avoiding bias/discrimination, transparency of AI decisions, and respect for employee and customer rights. For instance, if you use AI in HR, perhaps you commit that a human will always make the final hiring decision and that candidates can opt-out of AI-based assessments. Setting these rules reflects your cultural values (e.g. fairness, accountability) and builds trust. You may want to form an “AI Ethics Committee” or task your risk management team to oversee AI deployments for compliance and ethical alignment. Additionally, clarify new roles and decision-making authority in processes that involve AI: who is responsible if the AI makes a wrong prediction? When should employees override an AI recommendation? Make it explicit that employees are empowered to question or challenge AI outputs – this keeps the culture one of active engagement, not passive submission to “the machine.” By establishing guardrails, you not only protect against disaster, you signal to everyone that you’re implementing AI thoughtfully and responsibly.
Reinforce Cultural Values at Every Step of AI Adoption: During all these changes, continually tie actions back to culture. When you hold training, open it with a message about how this upskilling reflects your value of growth and learning. When you run a pilot, close it by discussing how the outcomes align with your mission to serve customers or collaborate better. Essentially, narrate the integration of AI as a chapter in your ongoing culture story. If your culture is very people-centric, find ways to involve employees in shaping AI rollouts (e.g. get feedback from end-users, form an employee advisory panel on AI). If your culture values innovation, host hackathons or innovation days to let teams play with AI tools and invent solutions. Every initiative is an opportunity to say, “This is who we are, so this is how we’ll do AI.” And don’t be afraid to adjust course if something feels off culturally. For example, if an AI tool is technically successful but employees hate it and it clashes with your values, be ready to pivot or even scrap it. Show that culture leads technology, not the other way around, through your decisions. As one expert succinctly put it: AI can measure and enable a lot, but “it cannot substitute for good culture.” So double down on your cultural strengths and use AI as a tool to express them more powerfully.

By taking these actions, middle market leaders can intentionally shape the intertwined evolution of their culture and AI capabilities. This intentionality is the difference between companies that end up with alienated employees and a jumble of tech…and those that emerge with a unified team, human and digital together, moving faster and smarter toward their goals.

Conclusion: Culture and AI – Your Twin Levers of Advantage

The question, “Which will shape which?” isn’t a binary choice at all. In reality, culture and AI will continuously shape each other in your organization. The companies that thrive will be those that actively manage that relationship rather than let it happen by accident. As a CEO or board leader, you have a profound opportunity (and responsibility) to ensure this interplay yields positive outcomes: a stronger culture and smarter AI adoption, feeding into each other.

Middle market firms may not have the tech budgets of giants, but you possess an invaluable asset: the ability to be more nimble and purpose-driven. Your size can be an advantage – you can adapt culture and implement new tech faster than a lumbering Fortune 500, if you lead with intention. By leveraging your cultural strengths – agility, closeness to customers, an entrepreneurial spirit – you can punch above your weight in the AI arena.

So, will your company culture shape your AI, or will AI shape your culture? The provocative answer is “Yes – both – so lead accordingly.” Set a vision where your culture shapes the use of AI to serve your business and stakeholders. And embrace how AI can shape your culture to be more innovative, data-informed, and future-ready. Don’t leave it to chance. With thoughtful leadership, you won’t be pulled in one direction or the other; instead, you’ll create a flywheel where culture and AI reinforce each other, driving your company forward.

In the coming years, virtually every middle market company will have access to similar AI tools. What will set you apart is how you use them – and that traces back to your culture. Lead with purpose, keep your people at the center, ask the hard questions, and take action to align technology with identity. Do this, and you won’t have to worry about whether AI is changing your culture in unintended ways. You’ll be too busy reaping the rewards of a culture that confidently wields AI as a competitive weapon – and of an AI strategy that elevates everything special about your culture.

The future belongs to the organizations bold enough to marry the heart of their culture with the head of AI. As a leader, the choice is yours: orchestrate that marriage with intent – or risk an unhappy collision. The companies that choose to orchestrate are already positioning themselves ahead of the pack. Now is the time to ensure you are among them. Your culture and your AI can either clash, or together, they can compose a symphony of performance. It’s up to you to conduct the tune.