What Professional Services will look like in 2030

Staff at the big consultancies are under pressure to show they are using AI, with some threatening to exit employees who aren’t willing to embrace change. The 2026 SPI Benchmark shows why there is urgency because the top 20% of professional services firms now generate more than double the revenue growth of their peers. One of the clearest separators is how — and how seriously — they are using AI. And yet SPI's own research finds only 1 in 10 firms is pursuing truly transformational AI. The rest are optimizing at the edges. This may be because firms still have not yet defined what AI-enabled knowledge work will look like in the future, both in terms of how they operate and how they deliver services to clients. It is quite telling that the 2026 Thomson Reuters survey suggests only 18% of professional services firms are tracking return on investment in AI tools, but 77% track internal costs, 64% track employee usage. This suggests what they are measuring is operationally and internally focused which is underline by the research as less than 23% track project internal revenue or new business won (17%).

Incremental vs transformative change

There is little dispute that you could do the same work with less people using automation. Or you could do more with the same people, increasing productivity. However, these approaches will only generate incremental results. If we are to believe AI is the step change vendors suggest, then surely, we need to rip up the professional services playbook and reimagine the value delivered to clients?

Transformative change should be the focus and explaining what the professional services firm of 2030 will look like. Otherwise, it should be no surprise that clients will question currently billing models if the focus is purely on operational efficiencies. Major consultancies, like PwC, have already admitted to passing on savings to clients gained through AI, but if margins are not to suffer it increases the need for AI use cases that generate unique value clients are willing to pay more for.

The major firms are moving quickly to demonstrate their AI credentials. PwC has launched PwC One which talks about “…moving beyond episodic projects toward more continuous insight, faster learning cycles and earlier visibility into risk and opportunity.”

Meanwhile, Accenture’s CEO is claiming the company is becoming “the most AI-enabled company in the world” where employees will only be considered for promotion if they show they are using AI.

Foundations for change

These are bold steps indicating that we are moving rapidly from the experimental phase to full production use of AI. Yet, if the industry is going to see radical change in the next few years, there are fundamental questions to be addressed. Firstly, do firms have the right technology foundations in place to respond to the potential opportunities AI will offer?

In the 2026 SPI Benchmark the high performing firms understanding it is not just about adopting AI but building it on top of integrated systems. The firms without these foundations are scaling AI tools on top of fragmented data. Logically, if applications cannot talk to one another it is hard for AI tools to extract data via APIs. It boils down to having a single view of all the data in an organisation. This requires integration between systems, a proper master data management strategy and a robust governance model to ensure ethical use of AI tools.

The core applications supporting the business must be able to grow with the organisation over the next five to seven years, because this agility is critical in such unpredictable market conditions. The major advantage for smaller and mid-size firms is that they do not have the vast disparate IT infrastructures of the big consultancies. With the right approach they will be able to adjust their IT strategies more quickly to exploit opportunities in specialist areas and develop new AI-enabled services that it may take the bigger firms much longer to initiate.

Measuring success

This leads to another fundamental question: understanding how professional services firms will make money if AI does have such a fundamental impact on the way services are delivered. The PwC Global CEO Survey in January suggested that only 12% of CEOs have both decreased costs and grown revenue using AI, so it is still early days in understanding how the technology delivers value. However, it is critical to take the billing model question seriously now rather than postpone discussion to a future date, because it will require a rethink of how firms measure success.

There is already much discussion around outcome and output-based metrics. The former would measure how a project improved revenues, reduced costs, or increased productivity. Once the project is successful completed, the delivery firm would take a fee based on a percentage of benefits accrued by the client. From an IT perspective if this approach is to succeed the AI will need the right framework, insight-rich data sources and handlers guiding the investigation. This requires critical thinkers who have an investigative, creative mindset and are good at delivering problem-solving services.

Output or time-based metrics will see AI automating significant elements of a task and results will be measured on completing projects within a certain timeframe. With significant automation of workflows, it could lead to a new generation of outsourcing allowing much smaller players to compete with the likes of Tata Consultancy and Infosys. It could become a very modular approach with clients buying resources off-the-shelf for specific tasks. It will require IT systems with very user-friendly interfaces to make it easy to use specific packages and it will also need to be supported by experts with specific task knowledge to ensure the smooth delivery of projects.

Building a creativity superpower

As the use of AI tools, such as generative AI and AI agents, increases there is also a danger that service delivery becomes more homogenised. If a firm is using the same tools across all its clients, how will consultants ensure the service delivered is unique for individual clients? Similarly, across the industry if AI-enabled services have the same foundations there is a danger that output becomes somewhat repetitive.

There are obvious ways to set up tools and models to tailor them to an individual project or client, but it does suggest that creativity could have even more value to the professional services firm of 2030. Understanding how models work, especially how to train them to be more relevant to niche topics or specific audiences, could become a superpower. It will require deep technical knowledge and the skills of an advertising creative director to manipulate data to produce new and unique ideas. Clients could measure professional services firms on the number of new creative ideas they generate and the revenue or market opportunities these innovative ideas trigger.

Ultimately, the changes we are seeing today could result in a very different approach to client engagement. Instead of having time-bound projects, consultants may need to build client relationships around continuous touchpoints using AI to offer more predictive solutions. Crunching data drawn from a wide variety of sources, the aim would be to present clients with “What if?” solutions that could create new opportunities before competitors identify them. AI-enabled technology would take on part of cognitive load for consultants, autonomously identifying patterns in real-time, leaving human operators to interpret and validate proposed strategies.

But what is clear is that firms need to act. The gap between top-performing professional services firms and the rest is not narrowing it is widening. The 2026 SPI Benchmark identifies three separating factors: leadership alignment, integrated systems, and intentional AI adoption. The Thomson Reuters 2026 report adds only 18% of firms currently measure whether their AI investments are producing results. Firms that build this measurement discipline now will have the evidence to justify further investment and the credibility to charge for the outcomes AI delivers.

About Eduardo Niebles

Eduardo Niebles is an accomplished ERP strategist and Senior Account Executive at Unit4, specializing in digital transformation for professional services organizations. With over 20 years of experience across five ERP providers, he has led and grown sales divisions globally, including managing operations in the UK, the USA, and Asia-Pacific. 

Eduardo holds a degree in Nuclear Engineering from the University of Florida and certifications in Artificial Intelligence and No-Code Machine Learning from MIT. His expertise spans enterprise software and technology for the professional services verticals, underpinned by a strong commitment to operational excellence and client success.

Eduardo is a frequent contributor to industry discussions on ERP modernization and AI-driven business solutions, and brings a global perspective to every engagement.

About Unit4

Unit4's next-generation enterprise resource planning (ERP) solutions power many of the world's mid-market organisations, bringing together the capabilities of Financials, Procurement, Project Management, HR, and FP&A to share real-time information, and deliver greater insights to help organisations become more effective. By combining our mid-market expertise with a relentless focus on people, we've built flexible solutions to meet customers’ unique and changing needs. Unit4 serves more than 4,700 customers globally across a number of sectors including professional services, nonprofit and public sector, with customers including Southampton City Council, Metro Vancouver, Buro Happold, Devoteam, Norwegian Refugee Council, Global Green Growth Institute and Oxfam America.

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