How AI Is Rewriting the Rules of Consulting

Why It Matters

The transformation forces consulting firms to redesign revenue streams, talent strategies, and client delivery models, accelerating competition and raising the bar for measurable impact.

Key Takeaways

• AI accelerates analysis, shortening consulting project cycles.
• Pricing shifts toward outcome‑based and revenue‑share models.
• Firms adopt diamond workforce, emphasizing mid‑senior expertise.
• South Africa faces data‑science talent shortage, altering hiring.
• Clients must align AI with streamlined operating models.

Pulse Analysis

Artificial intelligence is rapidly rewriting the playbook for management consulting. By automating data gathering, hypothesis testing and scenario modelling, AI tools compress what used to be weeks of spreadsheet work into hours, allowing firms to deliver recommendations faster and at lower cost. This efficiency is prompting a migration away from the traditional time‑and‑materials contracts toward outcome‑based pricing, including revenue‑share arrangements that tie consultant compensation to the client’s realized gains. The shift repositions consultants from providers of insight to enablers of implementation, forcing firms to redesign engagement structures and value propositions.

The labor model is evolving in parallel. Large firms are abandoning the classic pyramid of many junior analysts supporting a handful of partners, replacing it with a ‘diamond’ shape that concentrates talent at the mid‑senior level where deep technical expertise—particularly in data science, machine learning and cloud architecture—is most valuable. This rebalancing has triggered layoffs of junior staff in markets such as the United States and Europe, while regions like South Africa confront a scarcity of qualified data scientists, prompting firms to compete for a limited pool and to broaden hiring criteria toward hybrid business‑technology skill sets.

For CEOs, the message is clear: AI cannot be treated as a standalone project. Successful deployments require mature digital transformation, robust cloud infrastructure and clean, well‑governed data—foundations that many organizations are still building. Consulting firms that can combine these technical prerequisites with deep industry knowledge are positioned to capture the growing demand for outcome‑driven engagements. As clients increasingly expect measurable ROI, firms that master risk‑based pricing and deliver rapid, implementation‑focused results will dominate the next wave of consulting services, reshaping the competitive landscape globally.

How AI is rewriting the rules of consulting

PwC South Africa’s Mark Allderman

AI is reshaping the consulting industry globally, altering business models, project life cycles and how engagements are priced. Some of these changes are reflected in the local market, with the shift away from analysis‑heavy engagements towards the delivery of tangible outcomes the most significant among them.

“Patience has run out for the old consulting model centred on months of analysis, lots of PowerPoint presentations and a lot of very bright people running around telling clients interesting things – the days of that are definitely gone,” said Mark Allderman, cloud and digital lead at PwC South Africa in an interview with TechCentral. “That PowerPoint brick wall still has its place, but it needs to be much shorter and sharper.”

The adoption of AI tools has allowed consulting firms to speed up analysis using a combination of in‑house tools and publicly available data. Clients also have access to AI tools, allowing them to analyse their own business problems – sometimes at a proficiency level similar to what they would otherwise pay consultants for. The value from consulting has therefore shifted away from the “what is” portion of an engagement towards the “how to”, said Allderman.

This shift is reflected in the pricing models being explored across the industry. While many engagements are still billed using traditional time‑and‑materials and fixed pricing models, clients are increasingly embracing models that link remuneration to project outcomes. The most extreme form is a revenue‑share arrangement, where clients pay less upfront in exchange for a share of the returns from delivered products.

Rob Godlonton, CEO of iqbusiness, which offers consulting services alongside its IT delivery practice, said his company is seeing similar patterns emerge. Shorter project cycles mean consulting businesses can execute more engagements within a given financial year, and combining this with risk‑based pricing gives clients room to take on more projects, driving demand for consulting services higher. “We have to look at different ways of doing things and different business models with our clients,” he said.

Demand driver

The key demand driver at present is companies wanting to extract more value from AI. Many businesses are moving away from experimental implementations in favour of more focused, value‑driven projects with measurable outcomes.

“What I say to CEOs is: before you even get excited about AI, make sure you understand your business’s operating model, supply chains and the way your business works end to end. Throwing AI at bad problems or processes that haven’t been streamlined is going to get you doing bad things faster,” Godlonton told TechCentral.

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The precursors for successful AI implementation are digital transformation, cloud adoption and well‑structured organisational data. Allderman said demand across all three categories has surged, fuelled by organisations’ desire to incorporate AI into their processes.

AI is also changing how consulting teams are assembled. Internationally, the traditional pyramid model – characterised by many juniors supporting a few partners – is giving way to a diamond structure, where fewer juniors are hired and the bulk of the workforce sits at mid‑to‑senior level, often with deep expertise in specific technical disciplines. This has led to mass layoffs and reduced junior hiring at large consulting firms abroad.

Rob Godlonton

Allderman said this shift has been under way at PwC for some time, even before AI began reshaping the broader industry. But the international trend is not directly mirrored in South Africa, where skills profiles differ markedly. While markets like the US and Europe have an abundance of talent, South Africa faces shortages – particularly in high‑demand technical fields such as data science. Local firms are therefore hiring as much as the market can supply rather than shedding jobs.

Godlonton agrees. “We are still hiring, but we are looking for a different type of person because of AI. Beyond the specialists, there is more demand for people who understand both business and technology.

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“AI will change the industry by shifting what clients demand and what they expect. The types of people clients engage with will also change. Clients are going to expect what we deliver as consulting houses to be more outcomes‑driven,” he said.