How is AI changing the day-to-day work of consultants? Fergus McIntosh, Senior Consultant in our London office, focuses on solving commercial strategy challenges for B2B data and software businesses and has worked with clients across a wide range of industries. He shares how AI is transforming project work, collaboration, and strategic thinking, and why human expertise remains essential.
How has AI changed the way you structure and approach a typical consulting project?
Fergus: I think the biggest change is that project time is now spent in different ways. Efficiency gains in processing, organizing, and navigating information mean there is more time for strategic thinking and brainstorming, which is where a lot of the real value lies.
At the same time, the approach to internal knowledge sharing has evolved. When the team can query meeting transcripts, notes, and important files, it puts greater emphasis on capturing information systematically. This reduces the risk of single-person dependencies, where knowledge is siloed within whoever attended a given meeting. Instead, it makes insights more accessible across the team.
AI also brings greater ambition when it comes to exploring hypotheses. Some analyses require time-consuming manual tagging, especially when data is inconsistent. With AI, it becomes possible for us to tackle things more thoroughly and with more considerations, which opens the door to nuanced outputs.
What has surprised you most about working with AI so far?
Fergus: What has probably surprised me most is the breadth of use cases. It has become almost second nature before starting any task to think through: “Is there a quicker or better way to do this with AI? Which parts of the approach could be improved? What limitations would it have by doing it that way, and how can I adapt my original approach to overcome them?”
Not always, but quite often, there are indeed quicker and better ways to do things with the AI tools we have today.
Where do clients tend to overestimate or underestimate the impact of AI?
Fergus: A common misconception I see is that AI can substitute deep human industry expertise. In reality, that’s often overestimated – especially for data, information, and service providers, where a key part of the value proposition is their interpretation of current events.
From my experience speaking with businesses that rely on this kind of insight, AI is currently a supplementary tool rather than a replacement. This is particularly true given the speed and scale of geopolitical and economic shifts we’ve seen over the past five years, where human judgment and contextual understanding remain critical.
How do you see AI shaping the future of consulting in the next few years?
Fergus: Looking ahead, AI is already influencing the types of challenges we work on. From a project scope perspective, almost all strategic business questions now involve thinking about how to adapt an existing product or business model to a world of AI.
At the same time, the ubiquity of AI is likely to accelerate many of the foundational analytical tasks. This could shift the focus more strongly toward strategic discussions between stakeholders, particularly around how to interpret and act on insights.
As technology continues to evolve rapidly, and as organizations push to deliver on AI-enabled strategies, there may also be a growing emphasis on implementation expertise and planning.
But what I find most interesting, is how the methods we use to answer research questions might change. Will we still rely on Excel formulas to analyze data, or will we increasingly ingest files into pre-programmed GPTs and query outputs directly? Will surveys still be the norm in five years, or will we design prompts, assumptions, and response personas in large-scale models to simulate results with greater specificity? In client meetings, will analysts continue to provide answers in real time, or will it become standard to have bots in Teams calls offering context and insights on demand? I suppose it depends on who you ask.
How has AI influenced the culture and collaboration within consulting teams?
Fergus: Right now, we’re very much in a phase of adapting to what I’d call “the new possible.” Teams are constantly exchanging tips and tricks, learning from each other, and experimenting with how to best use these tools.
It’s a particularly exciting stage, because everyone has access to powerful tools, and people are continuously finding creative ways to apply them. It’s awesome to learn from others and discover new approaches that quickly become part of everyday practice.
How does Simon-Kucher train and enable its consultants to effectively use AI in their daily work?
Fergus: We’ve been given access to a growing range of AI tools and capabilities, and there’s a strong effort to keep everyone up to date on what’s available and how to use it effectively. This happens through regular training sessions, town halls, drop-in sessions, and spotlight case studies that showcase how others are leveraging AI.
At the same time, there’s also a culture of experimentation. Beyond these formal channels, we’re encouraged to try things out ourselves and share what works. That balance between guidance and freedom often leads to creative and effective applications.
Within our internal AI governance framework, we have an AI Knowledge Assistant that consultants can use to support proposal and project work, and we’re continuously testing and rolling out the latest advanced ChatGPT features. We also have access to a growing range of internal AI solutions, including custom GPTs tailored to specific use cases. Beyond that, colleagues can get involved in hackathons or experiment with new AI applications and agents being built via LangGraph, which further supports hands-on learning and innovation around AI.
What is your most useful AI hack or tip you would recommend to others?
Fergus: One simple but effective habit I’ve developed is to include a requirement in my prompts to state and explain the relative confidence level of any information being shared.
This not only helps me re-align the time spent validating and cross-referencing results, but it also ensures a quick distinction between facts and generalizations.
Is there anything else you’d like to share about working with AI in consulting?
Fergus: Given the pace of change, I wouldn’t be surprised if much of what I’ve shared feels out of date in three years’ time. But that’s exactly what makes this space so exciting.