Services Pricing Is Evolving For an Agentic World. Here’s How.

Agentic AI has sparked a competitive revolution across industries, forever changing how businesses operate.

Unlike generative AI, which 80% of companies have deployed without achieving a bottom-line impact, agentic AI can transform core processes and improve productivity by upward of 50% in some cases.

Service organizations, in particular, have a monumental opportunity to reinvent their pricing to reflect the new value they provide in an agentic world, where humans can offload manual and time-intensive tasks to AI.

But the window of opportunity is quickly closing as competition intensifies. Within the next five years, many agentic-first organizations will quickly gain market share and displace traditional companies built on outdated playbooks and resistant to accept the changed reality. Big brands of today may even no longer exist, and others will completely reinvent themselves to stay viable.

Decisions made at this pivotal crossroads today will make or break an organization’s long-term success.

To help your services organization stay ahead of these shifts and establish a scalable foundation for success with agentic AI, let’s explore why service pricing needs to change, how to restructure your team for this new reality, and tips for guiding customers and employees through the evolution.

The Shift Toward Value-Based Pricing in Services

The traditional approach to pricing services based on time and materials is giving way to outcomes and value, which are now delivered through people, products, and AI agents. End customers are interested in paying for outcomes rather than just capacity, and agentic AI is enabling companies to embrace this change.

As humans automate traditionally manual and time-intensive tasks with AI and augment processes to leverage AI intelligence, services teams can dedicate more time toward process innovation and service enhancement.

Looking at the technology industry as one example, services revenue has far outpaced product revenue, now representing two-thirds of total industry revenue. However, sales representatives spend 72% of their time on non-selling tasks, such as quote generation, administrative work, and manual data entry — all of which AI can address.

Manual processes like those across industries can now be handled autonomously with agentic AI:

• Law firms can radically accelerate and improve their document creation and due diligence processes.
• Accountancy firms can automate manual data entry processes and fuel data-driven intelligence for clients.
• Technology companies can develop and test highly advanced software faster than ever with powerful new tools.

These improvements deliver immediate operational benefits that are passed on to customers through faster service speeds, greater accuracy, and overall service satisfaction. And, importantly, less time spent on error-prone and manual processes means organizations can prioritize service enhancements and find new ways to attract and retain customers.

Becoming an Agentic Services Organization

By effectively blending human empathy and intelligence with the power of AI, teams can deliver higher-quality services. The key is to lay the appropriate foundation and address three areas:

Centralized data management

Agentic systems are effective only if they can access and act on an organization’s full, accurate data. This has been true with all AI applications, as organizations have grappled with disconnected tech stacks and data silos for decades.

The first step to transforming workflows with agentic AI is to ensure the AI models have access to all data sources that have a bearing on the outcome. There has to be a systematic effort to ensure bad data is weeded out to prevent AI from learning from bad data, thus causing it to make bad recommendations.

AI governance

Once your agentic systems have access to all your data and activation tools, the next step is to create guardrails and processes for AI agent development and activation.

Just because AI can handle a task does not mean it should, or at least not without oversight. The majority of teams agree that agentic AI works best when it collaborates with humans. The AI agents have to be treated like normal human employees to ensure they have the right level of autonomy and access.

Build a governance structure first by auditing AI deployment as a whole.

• What safety measures must be in place to protect customer data?
• When should team members not leverage agentic AI?
• How can they effectively partner with AI in their workflows?

Expand your governance protocols by working through individual use cases. Follow a typical workflow where AI can significantly reduce time spent or improve output, and document how AI can augment a human in that journey.

Change management

An agentic tech stack redefines what’s possible for teams, and it may call for a new team structure entirely.

Review your team roles and responsibilities to ensure everyone is positioned for success in your new model. Create a plan to adapt or evolve roles as your use of agentic AI scales. Assess what training or support your team may need to hit the ground running with your AI-powered toolset.

Collaboration and brainstorming will help team members overcome hurdles faster and find innovative new ways to activate AI to supercharge your services value.

The Golden Era of Professional Services

We are entering the golden age of professional services. Every organization has a powerful opportunity to move consciously toward intellectual discipline fueled by AI. In this reality, every organization will align around its customers’ needs, how it can deliver greater value through its services, and ways to integrate AI to continuously improve its workflows.

Everyone has a choice to continue charging in their own way, or to lean into agentic AI and create something entirely new and future-proof. Customers and team members deserve the latter.