Artificial intelligence (AI) is actively transforming the professional services industry. From consulting and IT to legal and accounting, firms are using AI to boost efficiency, generate insights, and reimagine how services are delivered.
But efficiency alone won’t define tomorrow’s leaders.
The real competitive edge will come from firms that embed AI into the core of how they operate—not just to automate tasks, but to scale the unique expertise that sets them apart. These firms won’t just use AI—they’ll develop AI Agents powered by structured, contextualised knowledge platforms that amplify their intellectual property (IP) and institutional knowledge.
Beyond Data: Scaling Human Expertise Through AI
Data may still wear the crown with AI—but in professional services, insight comes from experience. The most valuable knowledge in a Professional Services Organization (PSO) is often tacit: hard-won frameworks, client-specific nuance, and consultant intuition.
To stay ahead, firms must go beyond accessing data. They must codify and scale their internal expertise—ensuring AI systems can apply not just data, but judgment. This is the difference between automating decisions and augmenting them with institutional knowledge.
The PS Platforms of the Future: Moving Beyond PSA and ERP
Today, Professional Services Automation (PSA) and Enterprise Resource Planning (ERP) systems are foundational for PS firms and teams. They help firms forecast demand, manage resources, plan projects, bill clients, and analyze performance. Many now come with built-in AI modules that enhance planning, utilization, and operational insights. These will continue to add great value.
But these systems weren’t built to capture the real differentiator in professional services: expertise.
For firms looking to lead, PSA and ERP systems are no longer a competitive edge—they’re the baseline. The next generation of platforms will go further, designed to capture, structure, and scale human knowledge across the organization.
This is where a new category is emerging—AI-powered knowledge platforms, often linked to terms like Knowledge-as-a-Service (KaaS) or Cognitive Automation. Some refer to it as AI-as-a-Service (AIaaS), though that term doesn’t fully capture the nuance. At its core, it’s about codifying consulting expertise and intellectual property into structured, accessible formats that AI can use to deliver firm-specific recommendations at scale.
Unlike traditional systems that track the business of services, these knowledge platforms power AI Agents that act as consulting co-pilots—surfacing best practices, insights, and frameworks tailored to the firm’s own approach.
The goal isn’t just automation—it’s augmentation. These platforms help firms replicate their best thinking, scale it across teams, and deliver more consistent, high-quality outcomes.
Scaling Consulting Expertise with AI
For firms that want to move beyond automation and truly differentiate, the next step is building AI-driven learning loops—systems that continuously improve by learning from real consultant feedback.
This is how firms begin to scale not just delivery, but expertise.
Three key shifts will define success:
AI-Powered Knowledge Repositories Platforms that automatically capture, refine, and distribute firm-specific knowledge—case studies, methodologies, decision frameworks—across teams and projects.
Consultant-Centered AI AI isn’t replacing consultants—it’s augmenting them. Acting as a force multiplier, AI helps consultants move faster, work more precisely, and stay aligned to best practices without starting from scratch.
Human-AI Collaboration by Design The most effective AI solutions will work within ethical, legal, and governance guardrails—ensuring that risk, bias, and liability are addressed proactively.
Of course, “guardrails” will look different depending on geography, regulation, and intent. For global firms, that means navigating varying AI standards while staying ahead of both client expectations and compliance frameworks.
One increasingly urgent area is intellectual property risk. As AI Agents begin generating client-facing content, code, or recommendations based on prior work, serious questions are surfacing:
Who owns the AI-generated output?
Can AI accidentally expose confidential or proprietary data?
Are firms protecting the prompts, datasets, and training materials that fuel these models?
In high-sensitivity industries like fintech, legal, and cybersecurity, these aren’t hypothetical—they’re already boardroom-level concerns. Leading firms are investing in safeguards to control how AI learns, stores, and applies information.
When done right, responsible AI becomes more than risk mitigation—it becomes a differentiator. Firms that offer not just innovation, but assurance, will win trust and unlock new opportunities.
Why Clients Will Still Need Experts
Some clients may assume that adopting AI internally will reduce their reliance on external consultants. But in practice, that assumption rarely holds up.
Most organizations still lack the foundation needed to get full value from AI. What they’ll need—now more than ever—is guidance from experts who can bridge the gap between technology, data, and domain-specific strategy.
Here’s why:
Specialized Training AI is only as powerful as the expertise behind it. Consultants bring the domain knowledge and contextual understanding that generic AI applications simply can’t replicate.
Data Readiness Many organizations lack the structured, high-quality data needed for AI to deliver meaningful insights. External support is often essential to become “AI-ready.”
Contextual Intelligence AI can process information, but it doesn’t understand nuance—like risk appetite, cultural considerations, or client history. Consultants bring the human judgment and industry experience that AI alone can’t match.
The firms that thrive will be those that combine AI’s scale and speed with human insight and expertise. It’s not about choosing between people or machines—it’s about making sure AI is trained on the right knowledge, and used in the right context.
AI will help firms deliver faster, more consistent outcomes—but it’s still experts who will set the direction, interpret the results, and make the decisions that matter.
The Competitive Landscape: 2025 and Beyond
According to the SPI’s 2025 Professional Services Maturity™ Benchmark, professional services firms are feeling the pressure since AI’s emergence—and the cracks are showing:
Year-over-year revenue growth dropped to 4.6%, nearly half the 10-year average.
Project overruns increased by 18%.
Headcount growth slowed to just 1.9%.
Profitability (EBITDA) declined by 36%, raising the stakes for operational efficiency.
At the same time, AI adoption is accelerating. Firms using AI in areas like project management, forecasting, and resource planning are already seeing improvements in delivery accuracy and profitability.
The takeaway is clear: AI isn’t just a competitive advantage—it’s becoming the cost of staying competitive.
While lagging firms rely on legacy systems and fragmented processes, leading firms are embedding AI across the business to drive smarter decisions, better resource alignment, and more predictable outcomes.
And with tighter margins, shrinking headcount growth, and rising client expectations, firms need more than incremental gains—they need a step-change in how they deliver.
AI offers that opportunity. But only if it’s embedded with intent.
The Next Wave: Agentic AI and the Future of Professional Services
Over the next five years, AI will evolve from a back-office productivity tool to a front-line enabler of consulting delivery. The biggest leap? The rise of Agentic AI—systems that don’t just analyze and suggest, but act with a level of autonomy within defined parameters.
Unlike traditional AI, which focuses on pattern recognition and prediction, Agentic AI is about dynamic action. These AI Agents can make decisions, adjust strategies, and execute tasks based on goals, constraints, and evolving context.
This shift will be a game-changer, enabling firms to:
Scale expertise instantly – AI systems will apply institutional knowledge, past decisions, and best practices across teams—without losing nuance or quality.
Refine outputs in real time – AI will learn continuously from consultant input, adjusting its recommendations and surfacing sharper insights with every interaction.
Accelerate learning at all levels – Junior consultants will benefit from AI-generated prompts and guidance rooted in the behavior of senior experts and past engagements.
Beyond expertise delivery, Agentic AI will power new capabilities across the board:
Cognitive AI for Consulting – Moving from data interpretation to strategic thinking and scenario planning.
Autonomous Project Management – Predicting bottlenecks, reallocating resources, and optimizing timelines without manual intervention.
AI-Augmented Expertise – Providing consultants with instant access to firm-specific insights and industry intelligence.
Intelligent Content Creation – Enhancing—not replacing—expert-driven reports, frameworks, and recommendations.
Hyper-Personalized Client Engagement – Tailoring service delivery based on behavior patterns, historical context, and real-time inputs.
As NVIDIA CEO Jensen Huang recently said, IT departments will soon evolve into the HR departments for AI Agents—defining roles, onboarding them, setting responsibilities, and reviewing their performance, just as HR do for people.
That doesn’t mean consultants are being replaced. It means AI is becoming part of the delivery team. The best firms won’t be those with the most tools—they’ll be the ones that design their operating model for human + machine collaboration, with AI augmenting every part of the value chain.
This shift is already underway…
Deloitte’s Zora platform, announced last week, and built with NVIDIA, deploys domain-specific AI Agents across finance, procurement, and HR—executing tasks 24/7 and surfacing insights as they go. [Linked Press Release]
EY’s Agentic platform, similarly and also announced last week, supports high-stakes decision-making in tax, risk, and finance by embedding firm-specific expertise into reasoning models. [Linked Press Release]
These platforms aren’t removing people—they’re amplifying them, turning static IP into living, evolving systems that adapt to each client and engagement in real time, maximizing the impact the consultant can have. In this new landscape, Agentic AI won’t just support delivery—it will become part of the delivery team.
The Technical Shift: AI Tools and the Rise of Prompt Engineering
While most discussions around AI in professional services focus on client strategy and advisory, a quiet transformation is reshaping how technical solutions are delivered behind the scenes.
For consultants working on system builds, configurations, and custom implementations, AI is starting to change how work gets done. Emerging tools like Cursor AI and Windsurf are becoming part of the delivery stack—accelerating development, automating documentation, and enhancing testing.
This shift is laying the groundwork for a still-emerging role: the Prompt Engineer (PE).
Prompt Engineers aren’t just experimenting with prompts—they’re applying developer-level thinking to how AI systems behave. They understand how models interpret instructions, what influences their outputs, and how to guide them effectively. It’s a new kind of development—less about writing code line-by-line, and more about orchestrating intelligent systems that can generate and adapt code on demand.
Think of it like a pilot flying on autopilot: the autopilot may be navigating the skies, but a trained pilot is still at the controls—able to course-correct, override, or intervene when needed. Prompt Engineers play that role. They don’t just tell AI what to do—they understand how it’s doing it, and why it matters.
While not yet widespread, forward-thinking firms are beginning to embed prompt engineering into their technical teams, particularly in embedded services groups within SaaS and enterprise software companies.
As these tools mature, the lines between consultant, developer, and AI orchestrator will continue to blur. And those who can pair deep domain expertise with technical fluency in AI systems will be the ones leading the next wave of high-quality, scalable delivery.
What Will Separate AI Leaders from the Laggards?
Adopting AI is no longer a differentiator—it’s becoming a baseline requirement. What will separate the firms that lead from those that merely keep up is how deeply and intentionally they embed AI into their business model, delivery structure, and commercial approach.
High-performing firms won’t just use AI for marginal gains. They’ll use it to transform how they create value, drive innovation, and engage with clients.
Here’s what they’ll do differently:
Master Data Structuring Firms that can organize and operationalize their data—both structured and unstructured—will unlock the full potential of AI. This goes beyond dashboards; it’s about feeding AI with the right context and content to generate meaningful, firm-specific insight.
Continuously Optimize AI-Driven Operations AI won’t be a one-off implementation. Leaders will build feedback loops and learning systems that allow AI to evolve—improving profitability, scalability, and speed over time.
Train Professionals to Work With AI The future isn’t AI vs. consultants—it’s consultants who know how to guide, interpret, and shape AI outputs. Data literacy and prompt fluency won’t be niche skills; they’ll be essential across every role.
Use AI to Anticipate Client Needs Rather than react to client requests, leading firms will use AI-powered signals to spot opportunities early—enabling proactive, personalized, and strategic engagement.
Rethink the Go-to-Market Model The commercial model will shift. Forward-thinking firms will move beyond billable hours to offer Knowledge-as-a-Service (KaaS) or AI-powered subscription models—blending consulting expertise with technology delivery to create recurring value streams.
The firms that win will be those that don’t just adopt AI—they architect their business around it, designing every process, product, and client touchpoint to be enhanced by AI Agents, structured knowledge, and human expertise working in tandem.
Conclusion: A Strategic Imperative
AI is no longer optional for professional services firms—it’s a strategic imperative.
Firms that embrace AI today won’t just be more efficient—they’ll redefine how they deliver value, scale expertise, and engage with clients. PSA and ERP systems will continue to improve operational efficiency through AI-driven orchestration—but those gains alone won’t set firms apart.
The real inflection point will come from platforms that capture, structure, and activate human expertise—enabling AI Agents to deliver firm-specific insights, recommendations, and action.
In this next phase, data still wears the crown—but it’s AI-powered knowledge platforms and prompt-fluent professionals who will wield its power.
The question is no longer if AI will transform consulting. It’s who will lead that transformation—and how far ahead they’ll be when everyone else catches up.
About SPI:
Since 2006, Service Performance Insight (SPI) has been the leading authority on performance optimization for professional services organizations. As the creator of the Professional Services Maturity Model™ (PSMM), SPI provides proven frameworks, benchmarking data, and actionable insights to drive EBITDA, productivity, and scalable growth.
Our research spans five critical pillars of service performance—leadership, talent, client relationships, service execution, and finance & operations—and has helped over 50,000 organizations navigate change and scale with confidence.
At the core of this approach is the PS Maturity Assessment™: a data-backed roadmap for leadership teams to understand what’s working, uncover performance gaps, and accelerate improvement—benchmarked against industry peers and high performers.