Why strategy firms should watch their backs in the AI revolution

Behind both these statistics is a growing recognition that AI isn’t a one-size-fits-all solution. As clients learn from the application of this technology in their own organisations and from working with consulting firms, their sense of where AI can be best applied has shifted.  

Looking specifically at clients’ attitudes to how firms deliver their services, there appear to be three trends: 

• Words, not numbers – gathering and analysing qualitative data continues to be the area where clients expect AI to have the greatest impact. Clients are also more positive about the use of AI in writing reports.  

• Certain changes aren’t being felt – clients think AI will have less of an impact on certain consulting processes, such as benchmarking and the creation of computer code. That might feel counterintuitive to the firms already using AI to write better code faster, but such changes are invisible to clients. Clients may also have expected, but not received, a price reduction, and may be interpreting its absence as evidence that AI isn’t making a difference.  

• Supporting task management – AI is still expected to play an important role in project management, but more on the planning and task management side, and less on project communications.  

Clients’ changing assumptions about the use of AI will impact different firms in different ways. Technology practices, for example, might be wary of talking too much about the efficiency gains of using AI to write computer code, but will need to make the better results they get from AI more visible if they’re to remain competitive.  

But strategy practices will face the most pressure to change, and they potentially face the greatest challenge. While strategy work as traditionally done commanded some of the consulting industry’s highest fee rates, a large part of the work involves data gathering, analysis, and report writing. It’s obvious to clients and consulting firms alike that such work can be improved and accelerated by the judicious use of AI-enabled tools that are designed to support, but not replace, the clever people who use them. But those tools are only as good as the data they sit on, so the real opportunity for competitive advantage lies in more, better data. Better and faster analysis will be table stakes. 

The first and most obvious problem is that if clients and consultants are using the same data (“the internet”), the AI tools now available to clients allow them to do much of same analysis that they would have hired a strategy consulting team to do. Strategy consultants will still play a role, but it will be smaller and shorter, as highly expert and experienced interpreters of the data the client has pulled together. The logical response to this is for strategy practices to make more of their own, proprietary data—they’ve got something clients don’t have and that no amount of analysis of public data is going to yield. Some strategy practices are better placed to respond than others, with long-term, large-scale datasets of consumer behaviour, for instance, or benchmarking data that came with acquisitions. The larger strategy firms will fare better than mid-sized ones because they’ve invested more, for longer. Mid-sized and smaller strategy firms will instead have to rely on very specific datasets.  

However, other types of firms may have substantial datasets in other areas: HR firms in the people productivity space; technology firms in terms of adoption success; the Big Four firms have decades of industry performance data. Applying AI-enabled analysis tools to these unique sources of data puts such firms on a more equal footing with the strategy firms. They don’t necessarily have the brand to compete with traditional strategy practices when it comes to expert interpretation, but in the future battle for share of the strategy consulting market, that may be less important than it has been in the past. 

What can firms do next?

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