Written by Dr Alastair Jones, Leadership Consultant at Instep
AI adoption in manufacturing is at a pivotal moment.
The AI technology exists, the business case is clear, and the potential economic impact is significant, yet many food and drink manufacturers are still failing to realise meaningful productivity gains. The issue isn’t on the shop floor or a lack of tools; it’s leadership readiness. As highlighted by Skills England, manufacturing faces AI adoption challenges not because of technical limitations, but because many leaders lack the understanding needed to set a clear vision, build confidence, and lead their people through change.
The four skills that will enable successful AI adoption in manufacturing are the crucial leadership skills of clear communication, meaningful accountability, and effective delegation.
These are exactly the key leadership skills that great managers have always needed. AI won’t replace these skills, it magnifies their importance.
1) Communication: The Cycle That Never Stops in Leadership
When I first shared the Communication Cycle with a leader in UK food and drink manufacturing, his response was instant: “That’s my job, 10 to 20 times a day.” He was absolutely right. With constant turnover of starters, agency staff, and multiple production lines, his role wasn’t just to give instructions, it was to ensure messages were understood and acted on with precision. In food production, getting product through to packing correctly is non‑negotiable, and that precision depends as much on emotionally intelligent leadership as it does on automation.
Layer AI onto that environment and the lesson holds. Leaders who can’t clearly communicate an AI vision, or who rely on jargon instead of clarity, will see adoption stall quickly. The Communication Cycle, and checking for understanding through feedback, is just as critical to AI change as it is to the daily production briefing.
2) Accountability: Leading by Taking Ownership, Not Abdicating Responsibility
Accountability in manufacturing has often been associated with a blame culture of, “Who dropped the ball?”, “Who missed their target?”, “Whose line goes down the most?”
The most effective leaders know that accountability, when framed positively, is one of the most powerful tools they have.
Good accountability is supported by frameworks like the Accountability Ladder we use at Instep, which helps people move from a reactive mindset of “This happened to me” to a proactive one: “What will I do about it?”
In an AI context, this is critical since teams who feel change is being done to them will resist it. Teams whose leaders model accountability and acknowledge what they don’t yet know about AI while taking responsibility for upskilling, are far more likely to engage.
In the words of Brené Brown, “Anxiety is contagious, but calm is also contagious.”
The leader whose presence brings calm and perspective into uncertain situations, who manages their own emotional reactions before managing others, is the leader who creates the psychological safety needed for their team to experiment, make mistakes, and learn. Nothing matters more in the early stages of AI adoption than that sense of safety within teams and a culture of development not judgement.
3) Change: There’s Never a Convenient Moment
I recently had a minor operation on my foot. It wasn’t convenient, it disrupted two weeks completely and affected how I worked for nearly six. But I’d reached the point where pain was stopping me from doing things I enjoy, like hiking and cycling. So I planned ahead, took time off, and accepted short‑term disruption for long‑term gain.
AI adoption in manufacturing is similar. There’s never a truly convenient time for change, as production schedules, seasonal pressures, and competing priorities will always delay it. The leaders who succeed are those who plan intentionally, create space for transition, and focus on long‑term value rather than short‑term discomfort.
Time is critical. Many of the UK’s most skilled manufacturing workers are nearing retirement, widening the gap between existing expertise and the next generation’s capabilities. While initiatives are emerging, they won’t be enough on their own. AI can help bridge that gap, but only if leaders act now to put the right processes in place.
4) Delegation: Empowering Others With Clarity
Effective delegation has always been a hallmark of effective leadership, and in an AI-enabled environment, it becomes even more important.
Leaders who understand which decisions AI can support, which ones their team can own, and which ones require senior input will be far better placed to implement AI tools effectively.
At the same time, strong leaders need to decide which processes should use AI or not. Although it may be possible to provide a solution through AI, we need the boldness, if it is not morally the right approach, to say no when ethically a human is required.
The Delegation and Decision Tree model helps leaders and their team think clearly about where accountability sits and what level of autonomy is appropriate at each stage of a process.
In practical terms, this might look like an AI scheduling tool that optimises shift patterns, with team leaders empowered to action the recommendations within agreed parameters, while the site manager retains oversight of exceptions and any escalations.
Or consider demand forecasting: AI tools can model seasonal and promotional fluctuations with impressive accuracy, but a leader who hasn’t delegated will become a bottleneck, if every decision goes through them, rather than the one who enables their team. Clear delegation, backed by agreed decision-making frameworks, is what allows AI to accelerate operations rather than create a new hierarchy.
The Opportunity That Won’t Wait
The practical applications of AI in food and drink manufacturing are already being implemented and realised in the most forward-thinking organisations. From quality control and food safety monitoring to workforce planning and supply chain optimisation. But the common thread in every success story isn’t the technology, it’s the leadership that enables it.
Manufacturing won’t unlock the £400B AI opportunity by accident. It requires leaders who understand AI, embrace change, and model a future-ready mindset. Supporting them is not optional – it’s strategic.
Dr Alastair Jones is a former CEO, has a science D Phil and has been a leadership consultant with Instep since November 2017
