4-minute read

This Digest comes a little earlier than usual as I’ll be at the CIPD Festival of Work next week. We’ll be back to our normal fortnightly rhythm on 24 June.

This week I look at how AI and change are moving deeper into everyday work, especially frontline work, yet many organisations are still treating both as rollouts rather than human experiences.

New BCG data shows workers are using AI and worrying about what it means for their jobs. Starbucks shows what happens when technology meets real operational complexity. And McLean & Company reminds us that people can only absorb so much change before the brain starts protecting itself. Happy reading!

1. AI adoption is moving faster than organisational readiness

This tension runs through BCG’s AI at Work research, released today, and it should be a wake-up call for HR leaders.

The headline figure is striking: 61% of workers believe AI agents could do at least half their job within three years. This shows that this is no longer a distant debate about future skills or abstract productivity gains. Employees are already thinking about what remains of their role when large parts of the work can be automated, accelerated or handled by autonomous systems.

At the same time AI is moving into everyday work fast. BCG finds 74% of frontline workers are now regular AI users, up 23 percentage points in a year. This is an important finding because much of the corporate AI conversation still focuses on knowledge workers, office-based productivity tools and shiny pilots. The data suggests AI is already reaching the shop floor, service counter, warehouse, field site and customer-facing environment.

The issue for HR? Adoption is racing ahead of readiness. Some 88% of workers expect to need major upskilling in the next five years yet only 36% feel properly trained today. Half of companies have no clear rules for how humans and AI should work together. And 66% of workers receive no employer guidance on what to do with the time AI saves.

This last point is critical. AI-enabled productivity does not automatically turn into value. It can become better customer service, more learning, stronger problem-solving and more space for judgement. But it can also become faster work, rising expectations and greater strain. Without clear choices the gains will be uneven and the human cost may be underestimated.

The emotional picture is equally mixed. BCG finds 67% of workers say AI has increased their enjoyment at work while 41% say it has increased mental strain. In the UK the contradiction is even sharper: 70% of frontline AI users say it has increased day-to-day joy and satisfaction yet 49% fear losing their job to AI.

For people leaders this points to three immediate priorities:

1. Move the AI conversation closer to the work. Broad statements about transformation are not enough. Employees need to know where AI is expected, where it is allowed, where it is risky and where human judgement must remain visible.
2. Update skills strategies beyond tool training. Prompting may be useful but workers also need to verify outputs, challenge recommendations, spot bias, communicate uncertainty and know when to escalate to a human decision.
3. Make productivity gains explicit. If AI saves time, what should that time be used for? Better service? Learning? Innovation? Recovery from work intensity? If organisations do not answer that question then managers and employees will answer it for themselves.

👉 Read more on The People Space: Workers think AI could do half their job by 2029. Is HR ready? 5-min read

2. What Starbucks' AI retreat tells us about the frontline workforce

The BCG research shows that AI is already changing everyday work. This Starbucks story shows why this should make HR leaders pause.

Starbucks has reportedly retired an AI inventory tool across North America nine months after rolling it out. The tool was designed to automate stock counts and improve visibility of shortages. According to Reuters it had problems miscounting and mislabelling items, including similar milk types. Starbucks says the decision is about standardising inventory counting and improving consistency at scale.

This is a useful warning for every organisation putting AI into frontline environments.

Inventory counting sounds like exactly the kind of process AI should improve. It is repeatable, has rules and produces measurable outputs. Then you put it into a busy store, with product movement, storage variation, time pressure, customer demand, staffing constraints and the practical messiness of daily work and suddenly the question is not “does the technology work?” but “does it work here, in this job, under these conditions, with these people?”

This is where HR must get closer to the AI conversation. Too often frontline technology is treated as an operational decision. The tool is bought, piloted and deployed through technology, transformation or operations teams. But the consequences land on workers and managers. They have to use it, trust it, explain it, correct it and absorb the extra work when it does not perform as expected.

As we’ve seen, the BCG figures make this more urgent. Enjoyment and fear - this is the frontline AI paradox. Workers can see the value but they can also see the threat.

Steve Rockey, head of people and culture Europe at hotel group The Zetter, puts the human question well. Employers may look at AI to control labour management, stock control and process but for employees the question is simpler: does it make my life easier or does it create more aggro? This question should sit at the heart of every frontline AI rollout.

The other trap is treating the frontline as one workforce. The Josh Bersin Company identifies five types of frontline workers: customer-facing associates, back-office associates, high-skilled specialists, licensed specialists and credentialed professionals. Each group has different skills, risks, working patterns and technology needs. A single AI strategy for “the frontline” will miss those differences.

Five actions HR should take:

• Map the work before choosing the tool
• Bring frontline managers in early
• Let employees test AI in real conditions.
• Decide who can override the system when it is wrong.
• Measure trust, workload, error recovery and manager time alongside speed and cost.

AI could make frontline work safer, better supported and less frustrating. But the most valuable tools will be shaped around the people doing the work. The frontline is where many organisations carry their biggest workforce risks and their clearest opportunities for business value. AI makes understanding that workforce more urgent..

👉 Read my indepth report here. 6-minute read

3. Brain-friendly change

The Starbucks story is a reminder that technology fails when it is designed around process rather than real work. The same is true of change itself. Organisations often treat transformation as something to be rolled out, communicated and managed. New McLean & Company’s research suggests we need to look more closely at what employees are being asked to absorb, cognitively and emotionally.

Seven in 10 organisations are struggling to manage change, with too many simultaneous changes named as the biggest barrier. This suggests the problem is not simply poor communication or employee resistance but overload.

McLean argues that change needs to be designed around how people actually process uncertainty. The brain looks for safety and familiarity. New behaviours, systems and expectations can be experienced as threat, even when the change itself is positive. Change also adds cognitive load because people must learn, adjust, interpret and perform at the same time.

This reframes resistance. Too often resistance is treated as a mindset issue or a sign that managers need to push harder. A more human reading is that people are asking for clarity. What is happening? Why now? What does this mean for my work? What do I have control over? What is still unknown?

The research also strengthens the case for HR to be involved earlier in transformation. HR cannot sit downstream of decisions and then be asked to “land the change”. By that point, the pace, sequencing and employee impact may already have been set.

One of the most practical actions HR can take is to map the total change load before new initiatives are approved. Most change plans look manageable in isolation but employees experience them together. A technology rollout, restructure, budget pressure and new performance expectations may all hit the same team at the same time.

Leadership behaviour is another critical factor. McLean finds that when leaders are highly effective at managing change respondents are 1.6 times more likely to say they are not experiencing change fatigue. This puts change leadership firmly into performance territory. Leaders who create confusion, avoid difficult questions or overload teams carry a business risk.

So before asking people to change again ask what they are already carrying. What can stop, pause or merge? Where are expectations unclear? Which managers need support? Where are employees being consulted too late to influence the outcome?

Organisations have spent years improving the machinery of change. The next advantage will come from designing change around the human brain expected to carry it.
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👉 Read the full article here: Change fails when the brain feels unsafe. HR needs a more human approach. 4-minute read

Find your human space!

Siân

Editorial director, The People Space​

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