We recently convened a group of purpose and sustainability practitioners to explore how purpose led businesses are navigating the opportunities and challenges in deploying AI.

The specific questions we explored included how much voice purpose and sustainability has in decisions on AI deployment in their organisations, what can we learn from the successes and challenges in our work on purpose and sustainability over the last 10 or so years and how can we use these learnings to strengthen our ability to nudge the trajectory of the AI transition.

The key themes that emerged in the discussion are summarised below – including some practical and tactical things that practitioners could do right now:

Pace & agency: we can choose the pace:  There is a strong narrative of inevitability around AI: it is moving fast, everyone else is adopting it, so organisations need to keep up. But organisations have more agency than is sometimes assumed. There is an important distinction between velocity and trajectory. Moving quickly is not necessarily useful if you are heading in the wrong direction.

Tactics: Use your role to legitimise questions about pace and direction. Bring the longer-term perspective familiar from sustainability into AI conversations. Create permission for leaders to slow down or redirect, rather than equating caution with being anti-innovation.

The destination: what are we racing towards?  Speed of adoption is often equated with competitive advantage, but advantage towards what, and for whom? Conversations can quickly descend into licences, productivity, and use cases without asking the bigger question: what kind of organisation are we becoming? There is something strange about treating AI adoption as inevitable while simultaneously recognising that it could fundamentally reshape organisations and work.

Tactics: Connect AI explicitly to purpose, corporate strategy, and long-term value creation. Bring a future-facing question into investment and strategy conversations e.g. If we scale this approach, what will our organisation, workforce and customer proposition look like in five years, and is that a future we actively want to create?

The gap: from the “AI apocalypse” to Copilot licences: There can be extraordinary cognitive dissonance between the scale of the societal conversation around AI and everyday organisational decision-making. On the one hand, we are talking about human agency, jobs, inequality, and profound societal change. On the other: How many licences? What’s the productivity uplift? What’s the use case? Both conversations matter, but they rarely connect.

Tactics: Play the bridging role between these two conversations. Take live AI investments and connect them to existing sustainability priorities such as good work, inclusion, skills, human rights, customer vulnerability, or environmental impacts. Use existing materiality and stakeholder processes to bring the bigger questions into real business decisions, rather than creating a separate “AI ethics” conversation.

Sustainability as a partner, not the “fun police”:  Sustainability and purpose practitioners bring systems thinking, stakeholder perspectives, longer time horizons and experience balancing commercial and societal value. But being the person who arrives with another list of risks and guardrails is not always well received. The challenge is to throw a better party (!).

Tactics: Connect to people who already have organisational momentum e.g. strategy, digital, HR, procurement. Put AI into the sustainability or responsible-business strategy even if the organisation does not yet have a holistic approach to it. Use that as your licence to engage, and frame your contribution around innovation, resilience, opportunity, and long-term value, as well as risk.

AI is changing the customer proposition too: Much of the organisational conversation focuses on productivity, but AI is also reshaping relationships with customers. Efficiency for the organisation does not necessarily translate into a better experience for the person on the other side. As automated interactions proliferate, access to a knowledgeable human could itself become more valuable.

Tactics: Bring stakeholder voice into customer-facing AI decisions. Ask: Do our customers actually want this? Who might experience it differently? Where does human interaction create trust or value? Use existing customer research, inclusion, and vulnerable-customer processes to test assumptions before automation becomes the default.

Trust & character: perhaps the human stuff becomes more valuable: If AI makes technical competence increasingly accessible, then trust, judgement, relationships, and organisational character may become stronger sources of differentiation. Purpose, autonomy, and mastery could become more, rather than less, important. Trust may ultimately be one of the key assets that enables organisations to adapt successfully.

Tactics: Don’t immediately invent another set of AI metrics. Apply an AI lens to measures the organisation already has. Ask whether these indicators are strengthening or weakening as AI adoption grows and bring that evidence into discussions about productivity and performance.

The more interesting conversation isn’t just about efficiency: AI conversations can easily become trapped in “How many hours does this save?” But the bigger opportunity may lie in what becomes possible: new products and services, different capabilities, better-designed jobs, or more time for judgement, creativity, and human relationships. AI could also create opportunities to address complex social and environmental challenges in entirely new ways.

Tactics: Challenge narrow definitions of ROI in AI business cases. Alongside productivity, ask what new value is being created, what happens to the time released, whether work becomes better, and whether AI can accelerate existing sustainability or purpose goals. Make long-term commercial and societal value part of the opportunity case.

Governance: build the plumbing, not just the principles: Individual champions and responsible-AI principles will only take organisations so far. People move on, leadership priorities change and voluntary commitments can disappear. The deeper opportunity is to encode decisions about AI into the organisation itself, so that responsible choices become part of how the business operates.

Tactics: Draw on the experience of embedding sustainability and purpose into existing governance. Look at Board papers, investment committees, procurement criteria, risk registers, supplier due diligence, and workforce planning, and identify two or three points where inserting the right AI question could materially change an outcome. Explore emerging frameworks such as ISO 37011, which offers guidance on embedding purpose into organisational strategy, decision-making, policies, and processes, as a way of connecting AI choices back to the organisation’s purpose rather than creating a separate set of AI principles.

Boards may need imagination as much as information:  Board conversations about AI can quickly become dominated by technology, implementation, investment, and risk. But there is a more fundamental question about what AI does to leadership judgement and mastery itself. If Board papers are increasingly drafted by AI, summarised by AI and interrogated with AI, do we risk eroding directors’ depth of understanding of the businesses they govern? At the extreme, we could end up with something resembling “robots talking to robots”, with AI-generated information being consumed and responded to through AI.

Tactics: Use futures exercises to make the issue tangible, bring in fresh perspectives and ideas to challenge thinking.

Collaboration: remember that businesses have collective power
Organisations can feel like passive recipients of technological change, but markets are shaped collectively. Sustainability offers plenty of examples where businesses have collaborated pre-competitively to tackle problems they cannot solve individually. Similar collaboration around AI could help establish norms, influence suppliers and regulators, and create a sense that we are not all navigating this alone.

Tactics: Use the coalitions, sector relationships and convening power you already have. Identify a shared AI challenge that no single organisation can easily solve, such as workforce transition, responsible procurement, supplier expectations, or customer-facing AI, and convene a small pre-competitive group around it. Bring regulators, government, or technology suppliers into the conversation where that could help shift the wider market.

Fear is not necessarily a good mobilisation strategy (!): Purpose and sustainability leaders can play an important role in articulating what better looks like, while remaining realistic about the risks.

Tactics: Build a small portfolio of credible ideas that are ready when the opportunity arises: a human-centred approach to job redesign, questions for AI investment decisions, responsible procurement criteria, trust indicators, or principles for customer-facing AI. Move the sustainability contribution from “here’s why this worries us” towards “here’s a better way we could do it.”