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ZDNET's key takeaways
- Most IT leaders (82%) believe that data integration is a big AI challenge.
- Agentic AI pioneers use 10% more software applications.
- IT leaders will spend 19% of their IT budgets on AI agents this year.
Organizations are rapidly adopting autonomous systems. The average enterprise now manages 957 applications — rising to 1,057 for those furthest along in their agentic AI journey — with only 27% of these applications currently connected, creating a significant challenge for IT leaders aiming to meet their near-term AI implementation goals.
That's one of the key takeaways from the 2026 Connectivity Benchmark Report from Salesforce, MuleSoft, and Deloitte Digital. The eleventh annual report is based on survey data and interviews with 1,050 IT leaders globally.
Despite the widespread trend of agentic transformation, organizations face substantial obstacles. The primary challenges stem from complex, tightly coupled IT environments and accumulated legacy technical debt, which necessitates immediate process streamlining.
A significant consequence is that 71% of respondents reported that their systems are overly interdependent. This coupling critically hinders AI adoption, with data integration being cited as a major hurdle by 82% of respondents.
Companies that have fully embraced agentic transformation are utilizing significantly more applications than those still in the planning phase. On average, companies with full agentic adoption reported 1,057 applications, a significant difference compared to the 669 applications used by those in the planning stages.
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Yet despite this high volume of applications, connectivity remains low across the board. The overall average for connected applications was only 27%. The good news is that companies that have achieved agentic transformation demonstrated better integration, with nearly one-third (32%) of their applications connected.
Many organizations have data trapped across their application ecosystem. Trapped data translates to trapped value creation for employees, customers, and business partners. Business leaders must recognize that AI projects are data projects. The biggest threat to organizations optimizing their impact using AI will be silos — data, context, knowledge, and wisdom siloes.
Agents are everywhere
The report revealed that 50% of AI agents operate in silos rather than as part of a multi-agent system. That said, only 2% of IT leaders said they have no plans to adopt AI agent protocols, while agent-to-agent (A2A) and model context protocol (MCP) were used by 40% and 39% of respondents, respectively. Thankfully, integration is a key focus area — 86% of IT leaders said that, without proper integration, AI agents can introduce more complexity than value.
Organizations are rapidly accelerating their adoption of AI agents, with the current average utilization standing at 12 agents per organization. This rate is projected to increase by 67% over the next two years, reaching an average of 20 AI agents.
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AI agents have achieved near-universal adoption within organizations, with 89% of teams and functions reporting their use. This widespread implementation has led to a significant increase in IT budget allocation. Digital leaders anticipate dedicating an average of 19% of their IT budgets over the next year to initiatives focused on AI agents and agentic transformation.
Companies implement AI agents in three primary ways: using pre-built software-as-a-service (SaaS) agents (30%), integrating embedded agents in existing enterprise platforms (36%), or developing custom agents internally (34%). Effective AI agent implementation hinges on seamless data integration, a belief held by almost all IT leaders (96%).
Without proper integration, a large majority (86%) of IT leaders said they worry that AI agents could increase complexity instead of delivering value, underscoring the vital connection between data and successful AI agent adoption.
Roadblocks to agentic success
The report suggests AI transformation is hard. Nearly all (97%) IT leaders reported facing challenges with their agentic transformation projects. Access to trusted data is a key obstacle. IT teams now spend an average of 36% of their time designing, building, and testing new custom integrations between systems and data. Custom work will not help scale AI adoption.
The top challenges to agentic transformation included:
- Risk management, compliance, security, and legal implications — 42%
- Lack of internal expertise in AI and or AI agent design — 41%
- Legacy infrastructure or systems incompatibility — 37%
- Integration of siloed apps and data — 35%
- Business and IT alignment — 32%
The most significant obstacle to successful AI or AI agent deployment is data quality, cited as the top concern by 25% of organizations. Furthermore, almost all organizations (96%) struggle to use data from across the business for AI initiatives. Other key challenges included cybersecurity risks and the difficulty presented by outdated IT architecture or infrastructure. Most IT leaders (94%) noted that AI agents will require an IT architecture that is more API-driven.
Value creation at the speed of need
AI agents are delivering significant value, with 94% of respondents confirming they dramatically increase the speed and efficiency of development teams.
This efficiency gain allows the same percentage (94%) of IT teams to focus on higher-value tasks. Moreover, AI tooling is changing developer preferences: a large majority (90%) favor AI-assisted coding tools (like ‘vibe coding‘) over traditional methods for creating integrations and APIs. Despite this strong preference, organizations still face considerable obstacles, as 72% of respondents reported difficulties when attempting to leverage AI for system integrations.
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IT leaders said they expect AI agents to deliver several major benefits, including:
- Boosting employee productivity by automating tasks.
- Accelerating workflows and routine task executions.
- Simplifying complex systems and processes to enhance their management.
Furthermore, adopting AI agents provides organizational advantages that extend beyond technical teams. When non-technical users use AI agents, organizations see increased operational efficiency, decreased IT workloads, and better customer satisfaction and experience.
IT leaders are prioritizing an integrated end-user experience, with 83% already providing a connected experience across most of their channels. This emphasis is largely due to the anticipated impact of AI agents, which nearly all organizations (96%) expect to improve the employee experience.
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Organizations that have fully adopted AI agents are nearly five times more likely to report a significant improvement in employee experience (59%) compared to those still in the planning phase (12%). This integration of end-user experiences is already delivering measurable benefits, with over half of IT leaders reporting outcomes like increased customer engagement and improved operational visibility.
While 98% of organizations are committed to implementing AI agents and a strong consensus (95%) exists that these tools will increase development team speed and efficiency, successful implementation remains a significant concern. Nearly two-thirds (64%) of respondents said they are worried about their organization's ability to achieve its AI agent implementation goals.
Agentic transformation can involve a messy beginning, middle, and ongoing journey, but there is no end for now, as we are only at the very beginning of this shift. In an age of abundant innovation, the critical success factors will be culture, people, processes, and technology.
To learn more about the 2026 Connectivity Benchmark Report, you can visit here.
