AI at Scale: Why Culture Will Determine the Return
By Lynn Bennett, Managing Director, Advisory Services, Barrett Values Centre
Artificial Intelligence is no longer a future consideration. It is a present-day business imperative.
Across industries, organisations are investing heavily in AI platforms, automation tools, intelligent agents, and data infrastructure. McKinsey reported that 92 percent of companies planned to increase AI investment over the next three years, yet only 1 percent described themselves as mature in AI deployment, with AI fully integrated into workflows and driving substantial business outcomes¹. The foundations are being put in place quickly, while executive teams and shareholders look for productivity gains, faster innovation, and stronger competitive positioning.
Yet a critical question is often overlooked: Do we have the culture required for AI to create value at scale?
In our experience, this may be the single most important question an executive team and their board can ask before embarking on an AI transformation journey.
Technology can move quickly. People usually do not. Adoption depends on trust, confidence, changed behaviours, and leaders who are aligned on what AI is meant to achieve.
When those human factors are overlooked, AI initiatives often stall at the pilot stage and struggle to deliver sustained enterprise-wide impact. McKinsey's research on generative AI adoption makes a similar point: moving from experimentation to enterprise value requires organisational transformation, not simply new tools².
Many organisations still approach AI primarily as a technology initiative.
AI Transformation Is Also Culture Transformation
The real shift is not only technical. AI changes how people make decisions, share knowledge, use judgment, and take accountability. Harvard Business School Online describes AI adoption as a people challenge as much as a technology challenge, noting that trust must be earned in the algorithm, the developer, and the process³. Leaders cannot simply sponsor a new tool and expect the organisation to follow. They need to create conditions where people understand the purpose, trust the direction, and feel confident enough to work differently.
AI Does Not Transform Organisations. People Do.
AI changes how work gets done and how decisions are made. It reshapes how employees create value and challenge familiar processes, management practices, performance expectations, and professional identities.
As a result, the success of AI depends less on technical capability and more on an organisation's ability to adapt.
Organisations that scale AI successfully tend to have a few cultural conditions already working in their favour:
- People trust leaders enough to try new ways of working.
- Leaders are aligned on purpose, priorities, and expected behaviours.
- Teams are willing to learn, experiment, and adapt.
- Collaboration is strong enough to cut across silos.
- Governance and accountability are clear without becoming bureaucratic.
- Employees feel safe enough to raise concerns and ask practical questions.
These are cultural capabilities. Without them, even the most sophisticated AI investment will struggle to deliver meaningful returns. MIT Sloan Management Review and Boston Consulting Group have found that AI can produce cultural as well as financial benefits when organisations manage the relationship between AI use, culture, and organisational effectiveness intentionally⁴.
The Risks of Skipping the Culture Conversation
Many organisations complete technology readiness assessments, security reviews, governance planning, and vendor evaluations before implementing AI. Far fewer pause to ask whether their culture is ready.
This creates significant risk.
Risk 1: Low Adoption
Employees may have access to AI and still choose not to use it. LSE Business Review has argued that trust and technology acceptance are not enough on their own; employees may still resist AI when they are concerned about job security, autonomy, or the impersonal nature of the technology⁵. In day-to-day terms, people may be uncertain, overwhelmed, unconvinced, or fearful of making mistakes.
Without trust and confidence, adoption remains superficial.
Risk 2: Leadership Misalignment
Executives frequently have different assumptions about AI's role, purpose, and desired outcomes.
When leaders are not transparent and communicate inconsistent messages, employees receive mixed signals and implementation slows. Harvard Business Publishing makes a similar case for AI-first leadership, arguing that leaders need to connect technological capability to strategic goals, support human-AI collaboration, and build the capability required for adoption⁶.
Risk 3: Fear and Resistance
Employees naturally ask:
- Will AI make my role less relevant?
- How will my performance be evaluated?
- What decisions will AI influence, how much, and who will be accountable?
- Can I trust the outputs?
If these questions go unanswered, fear fills the void. And fear rarely produces innovation.
Risk 4: Scaling Existing Dysfunction
AI is shaped by the data, decisions, and assumptions that feed it. It can reinforce existing biases, automate poor processes, and speed up ways of working that may already be getting in the way. In practice, AI can turn cultural patterns into operating systems that run at scale.
In reality: AI scales whatever culture already exists.
If an organisation is collaborative and well aligned, AI can help that collaboration move faster. If the organisation is siloed, distrustful, or unclear on priorities, AI can amplify those conditions too. MIT Sloan Management Review and Boston Consulting Group's research supports this point: business culture affects AI deployment, and AI deployments can, in turn, influence culture⁴.
Technology magnifies culture. It does not replace it.
Risk 5: Ethical and Governance Challenges
Organisations that have not clarified their values, decision-making principles, and accountability structures are more likely to run into challenges around transparency, trust, data use, and responsible AI practices. Harvard Business School Online's guidance on scaling AI emphasises leadership alignment, governance, clear ambitions, stakeholder buy-in, and adoption metrics when moving from pilots to broader implementation⁷.
The issue is not simply governance. It is culture.
The Question Leaders Need to Answer
Before investing further in AI, leaders need to explore four core questions:
- What culture do we need for AI to succeed, and which values and behaviours must be strengthened or protected?
- How aligned are our leaders around AI's purpose, priorities, risks, and expected behaviours?
- Where are employees likely to experience uncertainty, resistance, or fear, and what trust needs to be built?
- Are we prepared to redesign work and decision-making, not simply automate existing tasks?
In other words: What is the required culture for our AI strategy?
This is where many organisations discover an important gap: they have defined the technology roadmap, but not the cultural roadmap.
Why "Required Culture" Matters
Every AI strategy carries an implied culture. An organisation that wants responsible experimentation needs a culture where people can learn, ask questions, and surface concerns early. Research from MIT Sloan Management Review and Boston Consulting Group reinforces the importance of organisational learning, finding that companies combining general organisational learning with AI-specific learning were better positioned to manage uncertainty⁸. Responsible deployment also requires clear accountability and ethical leadership.
If these cultural conditions are missing, implementation becomes harder and risk increases.
The question is not whether culture will influence your AI transformation. The question is whether you will influence your culture intentionally.
What If You've Already Started?
The good news is that organisations do not need to stop or restart their AI journey. Many have already begun implementing AI tools before fully considering the cultural dimensions of transformation. That is increasingly common.
The key is to understand where you are today and identify what may be limiting adoption, confidence, and value realisation. At BVC, we help organisations:
- Assess AI Culture Readiness by identifying the cultural conditions that support or hinder adoption, including trust, accountability, leadership alignment, learning orientation, collaboration, adaptability, and employee confidence.
- Define the Required Culture by working with leadership teams and key stakeholders to identify the behaviours and cultural conditions AI will need to create value in their specific business context.
- Align Leadership around a shared vision for AI transformation so leaders model the behaviours they need and expect from themselves and others to move change forward with consistency and intention.
- Identify Cultural Risks by surfacing resistance, uncertainty, trust gaps, change fatigue, governance concerns, and behavioural barriers before they become transformation roadblocks.
- Measure Progress through analytics and reporting that help leaders track readiness, engagement, trust, adoption, and cultural movement throughout the transformation journey.
The Human Advantage
As AI becomes more embedded in the workplace, one truth is becoming clear: lasting advantage will not come from technology alone. It will come from organisations that create the conditions for people to work well with AI, adapt with confidence, and use it in ways that strengthen human potential rather than diminish it. LSE research has also linked AI training with greater employee use of AI and reported productivity benefits, reinforcing the importance of capability-building rather than simply providing access to tools⁹.
A Question Worth Asking
As an executive leader, board member, or transformation sponsor, consider this: If AI were fully deployed across your organisation tomorrow, would your culture accelerate its success or limit its value?
If you are uncertain of the answer, now is the time to ask the question.
At BVC, we help organisations understand not only whether they are ready for AI, but whether their culture is ready for AI to create value at scale. Because successful AI transformation is never just about the technology. It is about whether people trust the direction, whether leaders are aligned and transparent, and whether the culture can support the change the strategy depends on.
References
- McKinsey & Company. Superagency in the workplace: Empowering people to unlock AI's full potential. January 2025.
- McKinsey & Company. Gen AI's next inflection point: From employee experimentation to organizational transformation. August 2024.
- Harvard Business School Online. How to Make Your Team More AI-Empowered. December 2025.
- MIT Sloan Management Review and Boston Consulting Group. The Cultural Benefits of Artificial Intelligence in the Enterprise. November 2021.
- London School of Economics Business Review. Successful AI adoption requires building employees' tolerance. November 2023.
- Harvard Business Publishing. AI-First Leadership: Embracing the Future of Work. January 2025.
- Harvard Business School Online. Scaling AI: A 6-Part Framework for Successful Governance. December 2025.
- MIT Sloan Management Review and Boston Consulting Group. Learning to Manage Uncertainty, With AI. November 2024.
- London School of Economics and Political Science. AI boosts productivity by the equivalent of one workday per week. October 2025.
