Consulting skills in the era of AI
Questions to consider
The ‘good’ ol’ days
It was 6.54 am.
I yawned as I stood in front of the train platforms at London Waterloo. Having decided I had no time to grab a baguette, before my train to Three Bridges. Instead, catching a sympathy smile from a fellow commuter.
50 minutes prior I had left home to begin the c.2hr commute to my first consulting assignment. Programme QA.
After 6 weeks of classroom theory, simulation, and discussion. I was eager for my first slice of on-the-job experience. Working with a grandfather-like South African, and a new manager.
Even with that brutal commute.
The ‘pay-off’ was a masterclass in stakeholder and vendor management...
Plus an introduction to the T-shaped skills framework. A way to look at how a consultant accrues both universal skills and spikes of specific expertise.
E.g., Breadth & depth of expertise across a competency (process re-engineering) or an industry (Education).
Helping us understand both business and how to develop our niche.
This was (is?) how new consultants cut their teeth.
Perform small, manual tasks that gradually build up into activities and jobs.
Use a mix of observing seniors, self-study, and applying your logic to deduce how to perform them.
Draw on curiosity, feedback, intuition, and experimentation to improve.
So naturally, a question we often hear is
“In the era of AI, how do consultants still learn?”
But first, what changes?
For the foreseeable future, the role of a consultant remains the same. Educate, advise, and, support clients to make a decision, then act upon it.
The onus is on consultants to:
Help clients be more data-driven in their decision-making,
Deliver more tangible outputs and,
Operate to the speed and impact that clients expect.
This aligns with the key skills identified in the 2023 MCA member survey. I.e., interpersonal, relationship building, behavioural science, data analytics, data science, sustainability, cyber literacy.
It also expands on the somewhat narrower narrative of skills you otherwise hear:
What about the next generation?
As the market outlook brightens and hiring resumes, Firms will of course welcome new joiners who are more accustomed to using Gen AI in much of what they do.
Their expectations on how they work and grow will bring a different tension.
At the same time, the technical skills they arrive with might also enable or boost a firm’s offering. E.g., Critical data analysis, and/ or Data science and/ or Deep AI.
So how do consultants still learn?
As they always have.
Through sufficient time, space, and structure.
To pique curiosity, instill belief, and apply learned competence.
A large part of answering this question is to use your firm’s experimentation with AI to review this as part of iterating your overall business strategy.,
What value are you putting against AI?
What % of financial savings will you re-invest into L&D?
How will you change how you deliver L&D? to protect skill building?
How will you balance your utilisation metric, with nurturing talent?
How will you manage your adoption of AI so that consultants have a playground to learn and adjust to the change?
In Discy, we believe that for many, AI shouldn't only be to get work done faster. It should be to help human consultants get better at the skills only humans have.
In this sense, AI is a workflow accelerant to help users think through more data than they otherwise could. To help them control where they spend their time.
E.g., As LLMs and Chat agents improve, consultants can analyse more data, faster. Without a large expense or needing technical data science or ML expertise. But with the literacy and confidence to deliver work that relies on AI. As well as to explain to clients why and when they have and haven’t used AI.
What next?
This week’s post is the first in a series that will delve more into the burning questions we’ve heard from consulting leaders over the past few months.
As always, welcome your thoughts and feedback in the comments!