A lot is written about the future of consulting right now. While many authors, announcing the end of McKinsey, BCG, and others, seem to have a limited understanding of the true role and value proposition of these organizations, there is clear evidence that their industry is indeed undergoing a bigger transformation.
In the first phase of the AI hype cycle, reports about headcount reduction and decline in the professional services industry dominated the conversation. Today, we much rather experience a big reshuffle in talent composition and delivery models. While many consultancies currently generate a significant share of their revenue through AI-related services, this could be a rather temporary spike.
From new operating models with “human + agent workflows” to “agent-specific governance for the AI era”: consultancies right now might, ironically, establish exactly the corporate AI infrastructure that will put their own business under pressure and force them to redefine themselves.
For decades, firms like McKinsey and BCG sold assurance and trust, maybe even more than strategy itself. While this aspect won’t go away in an AI era, however, professional service companies face a declining willingness of customers to pay for relevant parts of their work.
From professional services to “Service-as-a-Software”
At the same time, there are tremendous opportunities in productizing professional services, a trend now coined as “Service-as-a-Software”.
This goes far beyond automating the research and slide creation that a junior consultant would cover. Tasks that once required entire project teams are now part of intelligent systems that learn and improve across clients. AI systems permanently monitor vast amounts of data, enabling always-on advisory that proactively reaches out to leaders with alerts and recommendations. Specialized Agents are deployed for complex optimization challenges, like in product design, or to identify cost reduction opportunities along supply chains. Change management Agents understand team behaviors and provide highly personalized training content and coaching.
Nonetheless, it is still unclear who will be the long-term winners behind this shift. Even though the most prominent stories are currently told about the new challengers, there certainly will be relevant products from three directions. For many reasons, we have to count on the established consulting brands. At the same time, customers with their own in-house capabilities build a growing number of these services themselves. And there are the new entrants from the tech industry. Looking at Palantir’s growth or following OpenAI’s decision to launch its own consulting business, it is clear there is a lot at stake in professional services right now.
Having operated at the intersection of technology and services for almost 10 years, our teams at Workpath observe and drive these developments at the forefront. It is nothing but impressive how AI is already changing the way enterprises make decisions and operate.
Five Service-as-a-Software Opportunities of The “New SaaS” Era
At Workpath, we heavily invest in these new opportunities, and we can already see how they change operating models and the human-technology interface.
1. Services That Blend With Agentic Software
Consulting projects and customer experiences increasingly depend on seamless collaboration between humans and AI agents. Routine, junior-level work will be automated, while senior-level work will be amplified.
As AI takes over knowledge management and analysis, human value will shift toward mastering context, building trust, navigating politics, and driving implementation. Success will rely less on producing insights and more on turning them into results.
Industry frontrunners are already codifying their expertise into agentic software products, delivering them through new hybrid channels, and experimenting with more continuous consulting models and new approaches to pricing.
2. Services That Seamlessly Integrate With Workflows and Data Sources
The race in this new generation of professional services focuses less on building better AI models (which get commoditized rather quickly) and more on achieving deep integration with the implementation and maintenance layers of the enterprise. Seamless access to workflows and data sources determines the quality of any competitive professional service offering.
At the same time, time-to-value expectations are rising quickly, and clients no longer accept waiting or paying for months of data collection and analysis. They expect immediate advice and execution.
This requires new capabilities in consulting teams and redefines the role of IT in these engagements. As a result, leading service companies collaborate with CIOs to build the required infrastructure, establishing plug-and-play interfaces between corporate systems and their service products.
3. Highly Interoperable and Customized Services
Closely related to the previous point, we already see corporate IT teams driving the “Agentic Transformations“ of their infrastructure. They productize low-level services internally with self-built Agents and re-evaluate data strategies to strengthen centralized data control and accessibility for agentic use cases. IT also scrutinizes workflow tools to see how easily they could replace them with self-built AI or use them to provide context and guidance for increasingly autonomous agents.
Professional service providers must fit into this new ecosystem. Bringing their own closed team of consultants and agents for analysis and implementation won‘t be the norm anymore. Consultants have to master the orchestration of humans, data and agents in much more diverse cross-company settings.
4. Services Priced By Outcomes Rather Than Hours or Projects
While IT budgeting and corporate procurement only slowly embrace the new possibilities of value and outcome-based pricing, the pace of adoption accelerates. As companies automate low-level services internally and externally sourced services (partially) become productized, more data and opportunities emerge to establish new value metrics and charge only for actual results.
Initially, it was mostly IT budgets that were shifted towards AI investments. Now, budgets for headcount and human services are following the same path. This shift increases pressure on consulting firms to lower prices or change the scope of paid project activities. Successful service teams are able to offer new, yet simple and predictable pricing models that reflect this new reality, build on AI use cases, and tap into AI budgets.
Customers expect changes from their professional service partners
The CEO of a leading consulting company recently admitted on an earnings call: clients "expect some savings in productivity" from GenAI, with margins taking "18 to 24 months to recover." In this industry, productivity savings mean fewer billable hours.
The company's $3.3 billion acquisition of WNS hints at this new direction: WNS generates 24% of its revenue through outcome-based contracts and achieves 40-60% productivity gains through AI platforms.
Along the same lines, the Wall Street Journal reports that McKinsey has deployed around 12,000 AI agents, with outcome-based pricing now covering a quarter of its work.
5. Hyper-Personalized Services That Facilitate Better Transformations
One of the main reasons transformations fail lies in underinvested and poorly implemented change management. A painful truth behind many strategy execution gaps is that companies rarely spend enough time, attention, and budget to enable employees to overcome resistance and master change.
AI Agents and new conversational interfaces to interact with AI allow professional service providers to offer individual coaching to every employee within a client organization. No question will remain unanswered, and learning content becomes continuous, long-term, and highly personalized to each employee’s situation and challenges.
These new opportunities do not just make training and coaching more scalable, affordable, and accessible for all employees. They also reduce the tremendous number of failed AI initiatives, enabling smaller, data-driven starts and more iterative transformations.
Workpath’s Role In The New SaaS Era
At Workpath, we bet big on the service-as-a-software era. We believe in a long-awaited future where both new entrants and established consulting firms will play a role. Closely collaborating with our partners and customers, we invest in the corporate AI infrastructure backbone, as well as in the AI Agent layer.
As a foundation for hundreds of AI use cases, Workpath‘s goal graph provides third-party agents with critical information about strategy, priorities, and dependencies across all organizational levels. Our workflow platform enables enterprises to digitize their operating model and establish guardrails, rhythms, and data for better execution — not just for human teams, but also for AI Agents.
At the same time, we develop AI Agents like the Workpath Companion, which come with the skill sets of PMOs, market analysts, strategy consultants, and many more. We also enable executives and consulting partners to develop or enhance their own AI Agents using Workpath‘s technology and infrastructure. Through our AI Bootcamp, we support AI Transformation Leaders in upskilling their workforce and taking the first step into a future where, in most enterprises, more Agents than humans will execute work.
Tech Capabilities And Culture Will be Key To a Long-Awaited Shift
Since I started out in this space almost ten years ago, consultancies have been discussing asset-based service models, monetizing data, and staying more closely integrated with their customers. Yet there was only limited progress. One might argue that the technology was not there yet. Primarily, however, this is a challenge of culture and capabilities, as the transformation from service to product culture is difficult. Nonetheless, there is still space for traditional firms to adapt and reinvent themselves — if they act decisively now.
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