AI agents have become the primary driver of enterprise productivity. According to a recent report by Salesforce, organizations currently use an average of 12 agents, with that number expected to climb 67% within the next two years.
Currently, 83% of organizations report that most or all teams and functions have adopted AI agents. However, business leaders face stiff challenges in orchestration and governance. Around half of AI agents operate in isolated silos versus part of a multi-agent system. This has resulted in disconnected workflows and redundant automation. More than 4 in 5 IT leaders believe that AI agents will create more complexity than value due to integration challenges and silos.
These findings are from Salesforce’s 2026 Connectivity Benchmark Report, compiled in collaboration with Vanson Bourne and Deloitte Digital. The survey data is from interviews with 1,050 IT leaders across the globe.
The report highlights an expanding application database, with the average organization now managing 957 applications. Interestingly, the organizations that are further along their Agentic journey have 10% more applications. This suggests that as enterprises embrace agentic AI and have greater adoption, they also face greater integration challenges.
While the volume of applications is high, only 27% are “connected.” Salesforce refers to this as the Connectivity Paradox. Most enterprise systems may run at the same time, but they still cannot reliably share data, trigger workflows, or coordinate actions. As a result, AI agents often operate in isolation rather than as part of coordinated systems. This fragmentation makes it harder for organizations to turn growing AI adoption into real operational value.
Agentic AI is moving to a phase where connectivity is becoming a limiting factor. The next gains in productivity will depend less on deploying more agents and more on connecting them into systems that can work together reliably.
“The true success of an Agentic Enterprise isn’t found in the sheer number of agents deployed but the overall effectiveness of those agents,” said Andrew Comstock, SVP and GM, MuleSoft, Salesforce. MuleSoft is an integration platform Salesforce acquired in 2018.
“We need to think about how they are discovered, governed, and orchestrated to work together. As we move into this multi-agent era, the role of IT is evolving from managing silos to building a unified foundation as the central control plane that allows multi-agent systems to be safe, reliable, and scalable.”
The integration challenge is also impacting project delivery, with 26% of IT projects not delivered on time in the last 12 months. This has also resulted in a dip in productivity with IT teams requiring them to spend 36% of their time designing and testing new custom integrations between systems and data.
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As organizations find ways to overcome these challenges, the role of APIs is becoming more important. The report shows that 94% of leaders think that their IT architecture will be more API-driven. However, the data shows a disconnect in that ambition. Nearly one third of all APIs remain ungoverned within organizations.
Leaders want API-driven architectures, but many organizations are letting APIs sprawl without governance. This creates problems – shadow AI, security gaps, inconsistent data access, and more complexity. Shadow AI is where people use AI at work without the company knowing or controlling it.
According to Kurt Anderson, Managing Director and API Transformation Leader, Deloitte Consulting LLP, “This year’s Salesforce and Deloitte Digital research findings highlight a critical inflection point where organizations must move from simply deploying agents to operationalizing them at scale. Success requires reimagining integration strategies to build a foundation that is sustainable and secure. By establishing API-driven guardrails, enterprises can ensure their agentic transformation is ready for the demands of the modern enterprise.”
Emerging standards are becoming important as organizations try to connect isolated AI agents into larger systems. Many IT teams are already adopting new approaches, with 40% using Agent to Agent (A2A) protocols and 39% using the Model Context Protocol (MCP). Even so, keeping up is not easy. Nearly seven in ten (68%) IT leaders say they still find it difficult to stay current with new AI agent standards and protocols as they continue to evolve quickly.
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To address these challenges, many organizations are moving toward a more unified foundation built around APIs. The Salesforce report suggests that by treating APIs as the connective tissue of the IT environment, teams can link fragmented AI tools into a cohesive multi-agent system where agents can securely share data, maintain context, and operate across systems. APIs provide a practical way to connect applications, data, and AI agents across the enterprise, helping organizations move from isolated automation toward coordinated, scalable agentic systems.
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Author: Ali Azhar
