From backlog to breakthrough: AI agents are your IT force multiplier

AI agent adoption by function

The rules of IT have changed. Have you?

AI agents can take on up to 50% of your IT team’s daily tasks — an impact we’re seeing both in-house and with clients.

AI agents can deliver value by reasoning, solutioning and executing on their own. They can also work in teams. You assign them a high-level objective like debugging code, monitoring logs, organizing data or remediating an incident. Then, if they’re well-orchestrated, agents will plan each step, tap external tools and data, and carry out the work from end-to-end. Crucially, they learn from their actions and outcomes and they keep getting better over time.

In our IT transformations with clients, we’ve seen AI agents reduce effort, enhance user experiences and surface insights faster and more reliably. The result? Your people spend less time on routine operations and more time driving innovation and strategy.

These and other benefits can — and should — be tracked. AI agents deliver IT value across four dimensions: reduced costs, enhanced performance, rebalanced workload and a transformed workforce model. But to realize and prove that value, you need a clear baseline.

Start by capturing pre-AI metrics like cycle times, service levels, operating expenses, full-time equivalents (FTEs) and task volumes. This diagnostic phase sets the foundation. It helps reveal where inefficiencies lie, where value is hidden and what “good” should look like going forward.

Once agents are deployed, continue to measure. Critically, AI agents must unlock savings — not add complexity. Real value comes not just from automation, but from reimagining work — where agents absorb routine tasks and people shift to higher-impact roles. That shift doesn’t just reduce costs; it boosts speed, quality and satisfaction.

Where AI agents are reducing IT effort

From lines of code to lines of impact

Across IT, AI agents can take full ownership of some tasks, assist with others and leave the higher-value and higher-risk ones in human hands. In IT solution delivery, software development is one natural starting point. At one major retailer, for example, agents are reducing software development cycle times by as much as 60% and reducing errors by half.

In a traditional development cycle, IT specialists manage each step — from setting up the environment to debugging and testing. With agents in the mix, that workflow shifts. AI agents now take on repeatable tasks like cloning repositories, generating scaffolding, resolving common errors and running basic tests. Developers move faster, with agents as collaborators.

This frees IT specialists to focus on higher-value work: mentoring, reviewing code for quality and risk and guiding strategic decisions. AI agents don’t just support the process, they multiply its impact, enabling smaller teams to deliver more with greater speed, security and confidence.

Consider another example: portfolio and demand intake. Imagine a hybrid human–AI workflow that kicks off when an employee submits a request — whether to fix an issue or deploy a new app. AI agents then take over. One confirms receipt, another classifies the request and tags the correct business unit, a third mines internal datasets to draft a business case, a fourth verifies the data and flags any inconsistencies, and a fifth evaluates the proposal against IT’s portfolio priorities.

Only after this groundwork is done do human IT specialists step in. They review the AI-generated business case, decide on approval and set the priority. Across IT, similar AI-driven workflows handle rote tasks, freeing your team to focus on creativity, strategic thinking and nuanced judgment.

Don't just plug in AI. Power up performance.

A single AI agent can accomplish a surprising amount on its own — reading support tickets, retrieving account data, suggesting a fix and even following up. But the real power emerges when you orchestrate multiple agents into a seamless workflow to automate even complex processes end to end. When that orchestration spans functions, from IT to finance and beyond, it unlocks an AI-enabled organization.

In multi-agent orchestration, “manager” agents delegate tasks to specialized agents and assemble the results. A powerful orchestrator, like PwC’s agent OS, serves as the control plane for each of your agents, regardless of vendor. It provides a unified dashboard, built-in governance and centralized planning. You can improve token usage, swap in new agents or insert human intervention as needed. A good orchestrator will, in short, turn isolated use cases into well-governed and high-value enterprise solutions.

The new model: Smaller teams. Smarter agents. Bigger impact.

Your biggest risk with AI agents may be thinking too small. As AI agents take on more of the routine, repeatable work, IT teams don’t just get faster — they get fundamentally reshaped. In this new operating model, the traditional pyramid structure is flipped. In it, agents augment every layer of the organization, from support to engineering to leadership. The structure flattens, teams get leaner, and roles shift toward design, orchestration and decision-making.

You can roll out this model to capture value immediately and scale from there. Here’s how you do it.

• Work in new ways. Rethink workflows for hybrid human-agent teams, manage agent rollouts through agile sprints and make sure you can manage not just code but AI data and models as well.
• Embed trust. Manage the new risks tied to agent autonomy, intelligence and scale by building trusted guardrails: an orchestration layer and responsible AI.
• Align your tech. Add data upgrades, APIs and a scalable architecture as needed so you can power and oversee production-grade agentic systems.
• Futureproof your talent. Add new skills and roles, like AI product manager, agent engineer and escalation specialist. New hires might also include more creative, non-technical talent who focus on visual design, business requirements and communication.

With these measures, you can create a lean and nimble IT operating model. In this model, your people focus on strategy, high-value decisions and innovation. Under human oversight, agents do the rest.