Rethinking consulting in the age of Gen AI and AI agents
No longer a fringe experiment in consulting, AI has been transforming how firms operate, delivering both value and nurturing talent. Martin Colyer, director of digital and AI at LACE Partners, explains how consultants might reshape their business models as they adopt the technology at pace.
At our boutique HR consultancy, an evolution is well underway. Over the past year, LACE Partners has embedded AI agents and co-pilots into the firm’s daily workflows, using them as collaborators in a broader redesign of how consultancy services are delivered.
The result isn’t a radical departure from the consulting model, but a recalibration. Tasks once handled manually, such as workshop follow-ups, bid writing or sourcing internal methodologies, are now being streamlined by intelligent tools. In doing so, our consultants are reclaiming time for higher-value work to support our clients while also building new skill sets suited to a hybrid model of human-machine collaboration.
Where AI adds value
One of the clearest examples of AI’s practical use is in meeting execution. Our consultants spend hours in workshops or project sessions, then generate minutes, actions and task lists all of which is necessary and time-consuming. We’ve trained co-pilots to handle this routine admin, using transcripts and recordings to assign tasks immediately and distribute updates across teams.
Beyond hygiene tasks, co-pilots are embedded in day-to-day platforms like Excel and PowerPoint, supporting content creation, formatting and editing. This shortens review cycles, improves quality and reduces duplication. In parallel, bespoke AI agents have been built to sit over internal methodologies, allowing consultants to surface the right frameworks, templates and guidance on demand without having to trawl through files.
We haven’t limited these changes just to delivery. We have agents to support business development, too, cutting the time spent searching past work or formatting bid documents. What once took hours of digging is now condensed into a short query and a tailored output. Other agents assist in referencing public domain information and CRM systems, helping teams gather relevant client insights more efficiently.
All of this is underpinned by a structured change programme. We implemented an internal governance model with adoption champions, regular training and drop-in sessions. The company may be just over 100 people, but the approach mirrors what’s needed in larger organisations: building competence, supporting cultural adoption and offering the right interventions at the right time.
Testing, learning and adapting, from within
Critically, we didn’t launch this programme as a top-down technology mandate. Instead, we approached it as an evolving test-and-learn initiative. AI agents were introduced with a clear objective: to explore where they could genuinely support work. Our company has taken a methodical view, examining every process to ask whether an agent could sit over it and deliver value.
This internal experimentation has sparked broader reflection. As employees engage with the tools, they’re surfacing new opportunities and helping refine how the agents behave. This feedback loop is vital - not only does it improve performance, but it also helps ensure alignment with real-world needs rather than theoretical benefits.
Importantly, we’ve been highly conscious of reassuring teams about what this change means. The aim is not to erase roles, but to amplify what consultants are able to do.
The talent change
The rapid increase in AI agents’ integration begs the question: What is the future of junior roles? If AI takes on the kind of foundational work that used to build early-career experience research, formatting and note-taking, what becomes of the training ground for tomorrow’s consultants?
The reality is quite scary – indeed, in the consulting sector, entry-level jobs have fallen by a third since the launch of ChatGPT in 2022. However, at LACE, we’ve already thought this through. Our internal governance programme includes a strand focused on the talent pipeline, identifying which skills will need to evolve, be built or sourced externally. It’s a deliberate approach that considers not only how to interact with AI, but how to grow with it.
Prompt-writing, for example, is an extremely valuable skill. As was once true for learning mental arithmetic before calculators or mastering Excel functions before macros, there’s now a need to understand how to communicate effectively with intelligent tools. It’s a new evolution of learning - one that early-career professionals must embrace if they’re to thrive in a more digitised consulting environment.
Rather than viewing this as a loss of learning opportunities, we see it as an opportunity for reorientation. The challenge is not that junior consultants won’t have anything to do, it’s that the shape of what they do is changing. As AI handles the repeatable and the routine, juniors may find themselves stepping into more analytical, interpretive and judgment-based tasks sooner than before. As a result, the experience curve itself doesn’t flatten.
Value in human judgment
If the machine is taking care of the mundane work, does that mean clients will see less of the consultant? No. We believe that clients will continue to demand assurance, oversight and quality, and those remain firmly in human hands.
At the end of the day, clients want value. And as they begin using AI themselves, they’ll become savvier about what should be done by a person versus what can be handled by a machine. Firms charging for work that could be automated may find themselves challenged. The pressure will be on to demonstrate how AI is being used to increase efficiency and how that efficiency translates into either faster outcomes or more valuable insights.
Transparency will matter too. Consultants being upfront with clients about how AI is used, where it fits into the workflow, and how data is handled securely will be key. Our company has embedded this thinking into the approach: deploying AI in safe, effective and secure ways, while keeping the client relationship at the centre.
We are seeing first-hand what AI in consultancy looks like in practice: deploying co-pilots to relieve friction, building bespoke agents to support core services and actively rethinking the career paths that sit alongside these tools. The use of these tools raises deeper questions about how knowledge work is structured, how learning is sequenced and how client value is defined. For firms willing to embrace this experimentation, the prize is not just a more efficient business; it’s a more resilient, agile one - but only for those willing to build the right human systems around it.
