AI is now foundational to how businesses operate. The fastest path from experimentation to measurable value starts with executive alignment, clean data, and a CRM backbone designed for agents.
Across every executive conversation we have today, the theme is the same. How do we accelerate AI adoption, realize its value, and manage risk with trust at the center. Buyers are moving from proofs of concept to measurable outcomes, and leaders feel pressure on two fronts, move faster, and show impact. In our webinar featuring Forrester as a guest alongside Salesforce, the advice was consistent. Start now, start small, and build a foundation that connects AI initiatives to clear business outcomes.
The Market Moment
AI is no longer a trend. It is becoming foundational to front office operations, from sales to service to marketing. Forrester’s perspective is that three of the top five CRM operations priorities are now AI related, because AI helps create personal, high value experiences while lifting productivity and decision making in the flow of work. Organizations see gains in cycle time, content relevance, brand reputation, and customer outcomes when AI is coupled with trusted data.
Yet many teams still struggle to connect AI technology strategy to business strategy. The common blockers are familiar. Data privacy and security concerns, uncertainty about trusting AI outputs, gaps in AI governance, and limited access to the right skills inside the organization. Without a roadmap tied to outcomes, efforts stall and confidence fades.
“If you haven’t started, you need to start now. Start small with one targeted project, learn, continuously improve, and bring your people along.”
— Kate Leggett, Vice President, Principal Analyst, Forrester Guest
Why Programs Stall
We hear three consistent challenges from leaders across industries.
- Technical debt and legacy CRM. Old systems and fragmented processes slow experimentation and scale.
- Siloed and low-quality data. Insights are trapped in scattered sources. The right context is missing, and trust suffers.
- Process habits. Teams try to automate yesterday’s steps instead of asking whether AI can redesign the work entirely.
There is also a measurement gap. Only about half of organizations have benchmarks to assess AI performance, fewer than half have KPIs to decide whether to keep a feature, and roughly a third can link AI directly to profit and loss. That missing operational discipline is a core reason many AI projects disappoint.
Build the Backbone for Agents
Perficient’s point of view is simple. Do not just modernize CRM. Create an agentic ready CRM backbone that unifies Salesforce CRM, Data 360, and Agentforce to fuel agentic experiences across the enterprise. Put clean, accurate, actionable data at the center, and make iterative releases your default operating rhythm.
Salesforce’s customer zero experience shows what happens when you do. Sales velocity improved by about 36 percent with agents preparing briefings and eliminating repetitive work. Win rates lifted by roughly 11 percent as agents surfaced context and long-term memory at the right moment. Service agents now handle about 85 percent of inbound inquiries, which enabled a meaningful annualized cost takeout that was redeployed into higher value roles. Those gains start with a backbone designed for agents and the right trust controls in place.
“Be an agent boss. Set a big vision, pull it in tight to start, then scale as you learn.”
— Kaylin Voss, Executive Vice President, Agentforce and Data Cloud, Salesforce
Executive Alignment, Measured Weekly
Successful programs are not departmental mandates. They are board and CEO level initiatives that bring business and IT together, including your CISO. Establish top to bottom governance, agree on a weekly readout cadence, and develop a simple scorecard that connects input metrics, like coverage and cycle time, to outcome metrics, like win rate, average deal size, cost reallocation, and CSAT. If the executive communication cadence slips, momentum will not follow. Keep the drumbeat and iterate.
Start Now, Start Small
Choose one targeted use case that matters for revenue or experience. Land the agent where people already work, such as Slack. Give it trusted data and clear context by role and function. Put humans in the loop and coach the agent with rapid releases. This creates the flywheel for the next use case and prevents agent sprawl by keeping a learning architecture underneath your experiments.
And do not go it alone. Most organizations rely on vendors and partners to supply best practices, methodologies, and the hands-on support required to move from pilot to production with trust.
Your Next Steps
- Watch the on-demand conversation, then establish one clear goal for your organization.
- Book an Agentic Readiness Workshop to map the backbone, governance cadence, and a first use case tied to outcomes.
About this Series
This post is the first in our three-part series on moving from POC to outcomes, then measuring what matters, then scaling with people at the center. Subscribe to get the next article in your inbox.
