Billed to last: Why rapid learning is the key to consultancy growth

There’s always opportunity in change; even as technological advances place some roles under threat, others find new ways to diversify and make the most of the new landscape. Nelson Sivalingam, co-founder and CEO of AI learning and upskilling platform HowNow, explains how even when AI might seem set to steal its lunch, the consulting profession can leverage the technology to help upgrade the training that has previously future-proofed the sector.

Consultancy roles do, on the face of it, seem well defended from the depredations of AI. The profession relies on highly skilled individuals who often deal directly with senior clients – a combination of knowledge and interpersonal capability which has so far proved resilient to the job disruption caused by LLM and machine learning tech. But consultancy’s very selling point – that you’re buying the best, latest and most rigorous insight – makes it vulnerable.

The very rate of change driving the demand for consultancy – particularly digital transformation, technological risk management and complex analytics – opens up knowledge gaps. Do our best people have the time to learn? How do we ensure that they remain our best – that we retain our competitive edge – when volumes of knowledge are being created and supplanted at such a rate?

It’s worth noting that PwC, as an example, has diversified its advisory arm, expanding from four groups to eight. The implication – that appetite for consultancy will only grow in a rapidly evolving business environment – bodes well for those consultancies with the capability to learn and upskill at speed.

As businesses rush to incorporate AI-enabled tools into their tech stack and formalise AI tool use among employees, demand for consultancy services will only grow. But capability and knowledge need to grow in tandem, which presents a conundrum: how do we ensure that our consultants are keeping abreast of the innovation curve, while also contributing to business growth in the shape of billable hours?

Know what you know… and what you don’t

The skills mapping process has changed out of all recognition. What was once a laborious process driven by fleeting snapshots – for example, the ever-popular annual performance review – is now something that can be folded into the flow of work. Regular low-intervention reviews built into existing workflows, combined with AI-powered analysis of operational data, can provide a live and dynamic review of organisational capability – a far cry from the heavyweight spreadsheet which takes months to compile and is out of date by the end of the quarter.

Armed with a living picture of what your team does know, the same tools can drill into current market data to help you understand where the gaps are. Which skills are most in demand? Where are the skill bottlenecks in the job market? A project which might have taken your HR team several weeks can be done in hours with agentic AI tools capturing, analysing and summarising employment data and thought leadership articles. It’s never been quicker to unearth what your business does and doesn’t know.

Faster upskilling and real-time coaching

Once those gaps are highlighted, the balancing act begins. Your best people are also usually your best revenue generators, so ring-fencing time to learn almost always means losing money. But it’s now far simpler to fold that learning time into existing workflows. Low-touch, high-impact interventions powered by AI agents can effectively provide each individual with an always-on, infinitely patient learning coach.

An intelligent learning platform, underpinned by skills gap analysis, doesn’t simply recommend a course: it can plan and deliver a tailored learning programme based on high-quality, credible expertise from within your business and the wider industry. It can prompt a roleplay or conversation; take an in-depth look at a specific area or topic; revisit and refresh previously covered subjects and even find examples, analogies or case studies designed to mesh with the learner’s live projects.

In other words, this is learning designed to enhance what you’re doing right now. It’s about applying knowledge as you go: creating learning in theory and prompting you to apply it in practice.

Of course, your business may have the spending power to buy the knowledge and skills that it needs. The question is whether the talent is available to buy, and how expensive it may become. To take an example: tech roles, and particularly AI-related roles, are projected to create a major skills shortage in the UK. If the latest knowledge is so in demand, the price tag will be commensurately high. If you have the resources to compete on price with the Big Four, you may not need to worry. If you don’t, then boosting learning resources and creating intelligent upskilling workflows is not only more cost-effective – it’s a necessity.

Intelligent learning

For your very best people, this is a game-changing way to ensure that they remain your best. But the real point here is that this can be applied at scale, in a cost-efficient way. Intelligent learning can be integrated into onboarding, accelerating new hires’ path to productivity. It can be delivered as part of, say, a graduate or trainee scheme, mapping a clear route to readiness for your youngest team members. It works contextually, reacting to a learner’s knowledge level.

It takes account of live projects, using real-world examples to support ongoing, billable work. It’s the sort of always-on mentorship that the biggest companies invest in for their brightest and most promising talent, but now it’s financially accessible and available to every employee.

Ensuring the efficient deployment of resources presents an ongoing challenge for every organisation. For client-facing, knowledge-intensive industries, the trade-off between optimising revenue and boosting capability through learning can be a fine line to tread. Intelligent learning platforms offer a way to balance that equation.

Learning can be linked directly to live projects, offering context. Content can be ring-fenced or curated at a granular level, connecting learners with only the most credible knowledge and verified expertise. AI can even generate conversations, bringing learning to life through roleplay, Q&A and more. The pace of change is relentless. Without the ability to learn and adapt, we risk losing our competitive advantage: the edge which leads to success.