Enterprise businesses aren’t just experimenting with AI, they’re budgeting big bucks for it. According to a recent IBM report, IT leaders expect their AI spending to rise by 19% in the next year, with spending outside IT budgets projected to jump by 52%.
And yes, AI will make workflows dramatically more efficient. But these investments are also preparation for an agentic AI world set to take shape in the not-too-distant future. Experts predict it will include “a rich tapestry of AI agents, including personal agents, business process agents, and cross-organizational agents, work together to enhance productivity and collaboration,” writes Rajamma Krishnamurthy, a principal program management lead at Microsoft. Here’s what you need to know.
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Four Areas Where AI Agents Will Drive the Most ROI
As businesses build, deploy and train AI agents, they need strategic plans that align with business goals. After all, one agent can’t be expected to do everything, right?
Jim Wray, director and specialist of M365 Copilot program at Microsoft, say that IT decision-makers should zero in on four areas that drive the most business transformation.
- The Employee Experience: AI bots can improve productivity by 40% with the potential to “automate work activities that absorb 60–70% of employees’ time today,” notes McKinsey. But IT leaders still need to turn that time savings into revenue. “You’re giving people time back with AI,” says Wray. “But what are they going to do with that time? Will they strategize new solutions, mentor colleagues, upskill their technical skills or strengthen client relationships?” he added. Answering those questions is key.
- Reinventing Customer Engagement: AI can create more compelling customer journeys through personalized recommendations, predictive service and conversational support. But to measure results, teams must mine analytics from those experience platforms. “True value comes when leaders can connect AI use to measurable business outcomes,” Wray says.
- Reshaping Business Processes: AI agents are boosting productivity by 25% by speeding up routine tasks, compliance and daily workflows, according to this report. But IT leaders need to think beyond incremental automation and start to reimagine workflows from the ground up so that real-time data is part of every process. The next step is change management which requires that key talent be reskilled to align with the demands of a generative AI-driven world.
- Staying Ahead on Innovation: In today’s landscape, being reactive isn’t good enough; businesses need proactive AI strategies. Wray says to “set a value hypothesis” about how agents will deliver impact, pilot those programs and track the results against key performance indicators.
19%
The percentage by which enterprises are expected to increase their AI budgets over the next year
Source: IBM, “Embedding AI in Your Brand’s DNA,” January 2025
Your AI Agent Checklist
As IT leaders progress in their efforts, they may also find helpful a practical guide to assess readiness, build responsible frameworks and train employees. Here’s a checklist:
- Audit Current Use of AI: Understand where generative tools are already in use. This provides a baseline for formal adoption and security strategies.
- Migrate Strategically to The Cloud: To support scalable AI workloads, businesses must shift legacy data and infrastructure to the cloud.
- Create use case hypotheses: Identify high-impact areas where AI could deliver measurable value. Test these out with pilot programs and track results.
- Invest in Employee Training: Empower users with the knowledge to use AI tools responsibly and effectively.
- Implement Strong Governance: Secure your data, define responsible AI usage policies and stay informed about platform changes.
- Build an AI Center of Excellence: Partner with vendors, internal stakeholders, and innovation hubs such as CDW’s CTS services, the Azure AI Foundry and Qualcomm’s newest AI Stack to continually evolve your AI roadmap.
To unlock AI’s full potential across the enterprise, start small and iterate. “Early wins and proven ROI can help align stakeholders and build confidence,” Jonathan Rosenberg, CTO at Five9 tells BizTech.
Generative AI analytics can also help teams identify promising use cases and make sure that agents are continuously improving over time.
EXPLORE: How AI is empowering employees and IT leaders in the workplace.
“If an AI agent makes a wrong decision, it should be able to self-correct,” notes Vinesh Sukumar, vice president of generative AI and machine learning product management at Qualcomm.
Without this self-correcting mechanism, AI agents won’t be able to refine systems and improve processes and organizational needs as effectively.
“We’re working with a lot of enterprises to understand how we can scale agentic AI and optimize it for their workflows,” Sukumar says. “We are going to learn a lot.”
