09/09/2025
Remember when the workplace used to evolve gradually? There’d be a new digital platform or tool every few years, new processes and workflows now and then, maybe an occasional shift in reporting lines…
Ever since AI has entered the workforce, it often feels like the days of gradual workplace change are over. That may be because AI’s capabilities are already doubling every seven months. Everyday tasks like data analysis and customer support can suddenly be handled automatically and in a fraction of the time they once took.
For leaders, the question isn’t whether AI will change the workplace. It’s what type of workplace you want to create when it does, one where people can thrive through a strong working relationship with AI.
The “What” Versus the “How” of AI
We’ve all seen the countless hyped up LinkedIn posts, blog articles and news stories around AI: how it frees up employees from repetitive tasks, sharpens decision-making and accelerates innovation. Or, on the downside, how it creates mistrust, resistance and the risk of losing top talent to organisations doing it better.
Sure, there’s truth to all these claims. But when we devote all our attention to the “what” of AI (the end result), it’s dangerously easy to lose track of the “how”. That’s a major risk if you want to make AI agents into productive coworkers alongside your existing workforce.
Stephen Homer, Global Portfolio Manager for Digital Workplace at Getronics, argues that AI is more than just a new workplace tool. In his view, companies should treat it as a new type of co-worker. To get AI implementation right, it’s time to focus on “how” to effectively integrate AI agents into your teams and workplaces and establish a sustainable working relationship with AI.
Making Work Clearer, Not More Complicated
Most employees spend hours each week digging through reports, dashboards and emails, trying to make sense of the information they have on hand. AI can now step in as a navigator, quickly connecting the dots and delivering useful conclusions, whether it’s summarising meetings, spotting sales trends or flagging compliance risks in contracts.
As Stephen puts it:
“New AI agents are rational, goal-driven co-workers. They don’t just follow static rules — they think, they reason and they connect decisions to actions. That means they can complete tasks end to end, so your employees can focus on the judgments and creative problem-solving that humans do best.”
The difference comes down to how AI agents are embedded. If they’re integrated directly into everyday tools like Teams, they can flag recurring customer issues, pull up the right policy in a chat or generate meeting summaries on the spot. Built into document workflows, they can check contracts for compliance risks in seconds. But if they sit off to the side as yet another platform to log into, they add complexity instead of clarity.
Unlocking Skills and Multiplying Talent
One of AI’s greatest contributions to the workplace is the way it amplifies human capability. As Stephen says, “Think of AI agents as on-demand intelligence. They offer your employees the opportunity to continually learn, expand their knowledge, ask follow-up questions and get exactly the support they need in real time.”
AI robo-coaches are a great example. We’re already seeing the impact at companies that deploy AI work support tools for employees, such as Valence’s Nadia and CoachHub’s Aimy, which can be trained on company policies, contracts and other business data.
The world’s largest advertising firm, WPP, has rolled out Nadia to support its global staff in 36 different languages. Nadia offers fully personalised on-the-job support and answers complex questions whenever and wherever staff need. Instead of relying on old-fashioned search functions and FAQs, staff can now easily get answers through fast, conversational interactions.
Building Trust into AI Systems
A recent study by BCG finds that nearly half of employees (46%) consider AI a threat to their job. At the same time, AI adoption has peaked, with only half of employees using AI tools regularly.
If we want employees to see AI as a trusty co-worker instead of a threat, we’ve got to build trust and transparency into AI implementations from day one. That involves strategies like embedding agents into existing workflows, ensuring human approval for low-confidence outputs and keeping a full audit trail of AI agents’ actions.
As Stephen Homer explains, “It’s hard to build trust if you’re asking people to change everything they do. Instead, we should be augmenting the processes people already know, and making sure there’s always clear human oversight. That way, AI agents feel like dependable colleagues, not black boxes.”
Efficiency Where it Really Counts
With margins under pressure, many companies see AI as a chance to do more with less. But not every task benefits from automation – and, according to Gartner’s 2025 AI Hype Cycle report, only 30% of AI project leaders say their CEOs are satisfied with the results of AI implementation.
The real gains come from choosing wisely. Stephen suggests looking at three factors: how often a task is done, how complex it is and whether it follows a clear process. “The biggest efficiency wins come from tasks that people do all the time, that follow a relatively complex process and take effort to complete,” he explains.
That means activities like handling standard HR queries, checking invoices or producing recurring reports. They’re too demanding for basic automation, but structured enough for AI agents to manage reliably.
Creating Working Relationships with AI
The most powerful shift AI brings to the workplace in a new type of working relationship with AI. Employees are now collaborating with non-human agents that can learn, adapt and improve over time. This is changing how people see their own roles.
As Stephen says:
“Fundamentally, the employee shifts from being focused around data gathering and data processing into decision making and creative problem solving. Everyone becomes a leader, a manager and a coach of their own team of AI agents.”
This dynamic opens the door to more personalised work experiences. Over time, AI agents adapt to each employee’s personal preferences. When AI agents are well designed and genuinely useful, employees experience them less as software tools and more as dependable colleagues.
Getting the “How” Right
We’re all excited about how AI promises to transform the way we work. But gaining real value from AI requires careful planning and an employee-focused implementation strategy. Stephen recommends tailoring this 5-step approach to your employees’ actual needs and your organisation’s AI goals:
Prioritise the right tasks. Focus first on activities that are frequent, moderately complex and follow a clear process. These are where AI agents can add value quickly and safely.
Build a culture of trust. Clearly communicate that accountability stays with people. Celebrate employees who learn to collaborate with agents. Show employees that AI is their personal support system rather than a replacement.
Establish solid data practices. Reliable AI depends on well-governed, accurate data. Ensure teams understand their role in keeping information clean, structured and accessible.
Run contained pilots. Start small, measure outcomes and gather feedback from the employees using the agents day to day before scaling further.
Build an AI Ops function. Treat AI agents like digital employees who need oversight, authentication, audit trails and continuous improvement. An AI Ops hub or centre of excellence ensures accountability and long-term success.
By adapting the “how” to your organisation’s unique culture, workflows and ambitions, you position AI as a trusted co-worker that will deliver lasting value through a strong working relationship with AI
Talk to our team about how to prepare. We’ll help you put AI agents to work.
Frequently Asked Questions (FAQ)
Which types of tasks benefit most from AI?
Tasks that are frequent, follow a clear process, and are moderately complex tend to yield the best efficiency gains. Examples include recurring reports, standard HR queries, checking invoices, or compliance-related tasks.
What steps should organisations follow to implement AI agents successfully?
A recommended five-step approach:
- Prioritise the right tasks (frequent, moderately complex, structured).
- Build a culture of trust (communication, accountability, human oversight).
- Establish rigorous data practices (clean, structured data; governance).
- Run contained pilot projects to test and refine before scaling.
- Set up an AI Ops-type function (or centre of excellence) to monitor, audit, improve continuously.
