Accelerating the Adoption of AI Agents: Removing Data Silos and Unlocking Productivity
A recent survey of 1,050 CIOs revealed that 93% of IT leaders will implement AI agents in the next two years, with IT leaders working to implement the technology by focusing on removing data silos. This is a significant shift, as the average number of apps used by respondents was 897, with 45% reporting using 1,000 applications or more, hindering IT teams’ ability to build a unified experience. Only 29% of enterprise apps are integrated and share information across the business.
What are AI Agents?
AI agents are poised to accelerate the adoption of digital applications and create an epochal shift in human-computer interaction. According to ARK Invest, AI agents will:
- Understand intent through natural language
- Plan using reasoning and appropriate context
- Take action using tools to accomplish the intent
- Improve through iteration and continuous learning
Accelerating the Time to Value from Agentic AI
To accelerate the time to value from agentic AI, businesses can focus on removing data silos and leveraging a platform optimized for agentic AI development. According to Valoir, agentic AI promises to deliver exponential benefits from AI by automating complex tasks and interactions without human intervention. Valoir has defined seven phases of agentic development:
Phases of Agentic Development
- Model setup
- Data and application integration
- Prompt engineering
- AI guardrails and security
- User interface and workflow/application development
- Tuning
- Data accuracy
DiY vs. Deeply Integrated Platform
Valoir found significant differences between a Do-it-Yourself (DIY) approach and a deeply integrated platform with embedded agentic AI capabilities. Organizations taking a DIY approach use pre-built models, requiring three to 12 months to set up, while a deeply integrated platform like Agentforce requires little to no set up time, with an average of 7.5 times faster model setup.
Data Accuracy and Time to Value
Data accuracy is a key factor in time to value, the time needed to build and train AI agents to deliver acceptable levels of correct response. Valoir found that organizations using a DIY approach had accuracy rates of 50% for simple tasks and 40% for complex tasks, while a deeply integrated platform like Agentforce achieved accuracy rates of 95% for both simple and complex tasks.
Conclusion
In conclusion, the adoption of AI agents is poised to revolutionize the way we work, and businesses must prioritize removing data silos and leveraging a platform optimized for agentic AI development to accelerate the time to value. By understanding the phases of agentic development and the differences between a DIY approach and a deeply integrated platform, organizations can unlock the full potential of agentic AI and drive exponential benefits from AI.
Frequently Asked Questions
Q: What is the average number of apps used by respondents?
A: The average number of apps used by respondents was 897, with 45% reporting using 1,000 applications or more.
Q: What is the percentage of enterprise apps that are integrated and share information across the business?
A: Only 29% of enterprise apps are integrated and share information across the business.
Q: What is the average time needed to set up a DIY agentic AI project?
A: The average time needed to set up a DIY project is 75.5 months.
Q: What is the average time needed to set up an Agentforce project?
A: The average time needed to set up an Agentforce project is 4.8 months.
