What does AI mean for the future of consulting?

At Kindred we ran an office sweepstake for the women’s football World Cup (😢 Lionesses). To ensure teams were allocated randomly, we used ChatGPT to do the draw.

A few poor souls got Czech Republic, Slovakia, Chile, Poland and Croatia – teams, we soon realised, weren’t actually in the tournament. Clearly AI can’t do it all.

A recent report from McKinsey states that in the US, up to 30 percent of hours worked could be automated by 2030. Automation is unlikely to be evenly felt across all sectors and roles, but we were curious see where it might start to change our work.

To this end, we have been trialling AI in a few different contexts:

  • Transcription and note-taking (Otter)
  • Time management (Timely)
  • Qualitative analysis (Discy)

So far, we’ve found AI fairly useful, getting us some of the way there but never fully removing the need for human intervention:

  • Transcription software captures what a conversation sounds like but struggles to make sense of human communication filled with “um”s and “er”s, half-finished sentences, and words that sound a lot like each other.
  • Time tracking platforms can tell you how long you spent on a video call or working on a PowerPoint presentation but don’t know about the 1:1 you had over lunch or reading you did away from your desk.
  • Large language models give some pointers on what stands out in written data, but knowing that lots of people mentioned ‘strategy’ or ‘culture’ still leaves you plenty of analysis to do.

That said, there’s no doubt that with a little work and refinement, these tools have the potential to revolutionise certain roles and uplift others.

Where humans come in

Despite AI having the potential to disrupt knowledge work by carving out new avenues of productivity, it feels unlikely that humans will become obsolete. For many lines of work, creative and interpersonal activities remain crucial.

 Within consulting, for example, critical aspects of the job are still very much human-led:

  • Facilitating collaboration: Driving change isn’t just about taking in the data and spitting out the right answer, but creating environments where humans come together, listen to each other’s perspectives, and feel bought into the solution.
  • Navigating complexity: Deciding on the path forward involves several kinds of inputs, not just factual. It’s not just about the literal meaning of the words spoken, but the way they are delivered, and the surrounding context, too. AI is yet to prove its capability to effectively process all these types of data the way a human can.
  • Incorporating values: Decisions in organisations are often rooted in values which are intangible. For example, you may have a ‘gut feel’ about a new hire who, on paper, doesn’t tick all the boxes, but still manages to impress you because they show great initiative and attitude.

It’s clear that current applications of AI are not likely to replace the most important aspects of how most knowledge work gets done.

What we can expect

AI can potentially provide its users with unlimited data processing power and cognitive leverage. And while AI may assist the creative process or provide us with excellent productivity tools, it will struggle to create something truly unique, make important decisions that drive the future of the business, or give emotional guidance, coaching, and support.

The good news is that the better AI gets at removing transactional tasks, the more time we can invest in nurturing human skills and talents, including how to use AI for our benefit.

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