Some 700 million people now use ChatGPT every week. Now, the next phase of AI is well underway, as agentic AI undertakes autonomous task execution and multi-step, dynamic workflows. According to PwC’s AI Agent Survey, 79% of senior executives say their companies have already adopted AI agents, and two-thirds report measurable productivity gains.

That hype overshadows the reality for many, though, as failure rates for enterprise AI can reach 95%, according to one MIT study. Meanwhile, Gartner predicts that more than 40% of agentic AI projects will be canceled by the end of 2027 due to high costs, unclear business value, and inadequate risk control.

Why do some AI projects go astray?

Poor-quality data, a lack of organizational knowledge, and insufficient context can limit the effectiveness of agentic AI. Most AI agents can reach only structured data and the public internet — yet 80% to 90% of all enterprise data is unstructured and trapped in silos: PDFs, contracts, emails, manuals, and customer interaction records. Without that context, agents draw flawed conclusions and become a source of operational, financial, legal, and reputational risk.

“…agents draw flawed conclusions and become a source of operational, financial, legal, and reputational risk.”

If you’re a developer looking to build AI apps and agents the enterprise can actually trust, you’ll want to download our brand new eBook, The Developer’s Guide to Connecting CRM Data, AI, and App Experience at Scale.

What you’ll learn

Produced in partnership with Heroku, this eBook shows how to connect your AI agents to a complete, trusted data foundation — connecting Salesforce CRM data with enterprise context across the organization — so developers can ship context-aware AI apps fast, without drowning in infrastructure.

In this eBook, you’ll discover:

• Why the data foundation decides success or failure: Understand why access to CRM data alone isn’t enough, and how unifying structured and unstructured data builds the trust and context agents need to act autonomously.
• The accuracy-versus-latency trade-off: Learn how retrieval-augmented generation (RAG), built into Heroku’s platform-as-a-service approach, feeds fresh, verified data into models to improve outputs without sacrificing speed.
• How Heroku fits the Salesforce ecosystem: See how Heroku works alongside Salesforce Data 360 and Agentforce as an AI abstraction layer — letting you build with the languages and frameworks you prefer, free of vendor lock-in.
• How to collapse 14 steps into one: Discover how Heroku Connect, AppLink, Managed Inference, and Agents replace the complex integration, OAuth, and token-management work normally required to build apps on Salesforce.
• How to scale agentic AI securely across the enterprise: Get the blueprint to move from prototype to production, with platform-level governance, compliance, and built-in guardrails.

Why you should read it

Most AI projects fail not for lack of ambition, but because of the friction created by siloed data. This eBook gives developers a practical path to remove that friction — connecting CRM data to the rest of the enterprise, extending the power of Agentforce and Data 360, and deploying more sophisticated, context-aware applications with a leaner operational footprint.

Don’t let your next AI project become another failure statistic. Download The Developer’s Guide to Connecting CRM Data, AI, and App Experience at Scale today!

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