Accelerating Time to Agentic AI Value: Key Insights for Businesses

2025-03-03

As artificial intelligence (AI) rapidly transforms industries, businesses are racing to implement AI solutions that drive efficiency, improve decision-making, and enhance overall productivity. In particular, AI agents are gaining momentum as a powerful tool that can handle complex tasks autonomously. A recent survey of 1,050 CIOs sheds light on how businesses are prioritizing AI agents in their strategic initiatives, revealing some surprising insights into the challenges and benefits of this technology. With 93% of IT leaders planning to implement AI agents within the next two years, the race to harness their full potential is on.

This article dives deep into the findings of the survey, exploring how businesses are addressing the hurdles related to data silos, integrating multiple applications, and leveraging AI agents to accelerate productivity. It also highlights how specific platforms, like Salesforce Agentforce, are optimizing AI development, enabling organizations to significantly shorten the time to value and improve AI performance.

Key Insights from the Survey

A survey of over 1,000 CIOs reveals that the demand for AI agents is quickly growing, with 93% of IT leaders planning to implement them in the next two years. However, the vast number of applications used by organizations complicates AI implementation. With an average of 897 applications in use by respondents—and 45% of companies using 1,000 or more apps—integrating data across systems becomes an immense challenge.

The current state of enterprise data infrastructure is fragmented: Only 29% of apps share information across businesses, leaving significant room for improvement. In preparation for AI deployment, CIOs are allocating an impressive 20% of their budgets to data infrastructure—four times more than their AI budget, which is just 5%.

But what exactly are AI agents, and why are they such a hot topic for businesses? AI agents can understand intent through natural language, reason and plan in context, take action using tools, and continuously learn from interactions. With such capabilities, AI agents are poised to dramatically change how humans interact with digital systems.

According to ARK Invest, the adoption of AI agents will significantly boost productivity. Between now and 2030, businesses are expected to invest heavily in productivity-enhancing software, with global software spending potentially accelerating to annual growth rates of up to 48%.

What Undercode Says:

Undercode has always been focused on the value of cutting-edge technologies in streamlining operations. From the perspective of organizations seeking to adopt AI agents, it’s clear that while the benefits are immense, there are significant hurdles in reaching full implementation. The fragmented nature of current enterprise data systems remains the most significant barrier to AI success. Even though a majority of businesses are poised to integrate AI agents, data silos and the complex web of apps and applications that make up the business tech stack complicate the implementation process.

The findings point to a clear trend: businesses that invest in AI agents early, and integrate them into their workflows efficiently, will have a considerable edge over their competitors. However, the time to value—how quickly businesses can see tangible returns on their AI investments—remains a critical metric for success. The importance of data integration cannot be overstated, as businesses will need to break down these silos to fully harness the potential of AI.

A major takeaway from the report is the speed at which AI agents can be developed and deployed when organizations leverage specialized platforms like Salesforce Agentforce. The study found that the development process is 16 times faster compared to more traditional, DIY approaches. This is particularly important when considering that accuracy and trust are key to AI’s effectiveness. In this context, using a deeply integrated platform drastically improves both the development speed and the accuracy of the AI agents.

DIY approaches are slower, as teams struggle with model setup, data integration, and training. These manual processes can take up to 12 months to complete, whereas using a pre-integrated platform reduces this time significantly, providing businesses with better and more accurate solutions faster. Trust also plays a crucial role in the transition from generative AI to agentic AI. While DIY solutions require long hours to build trust layers, integrated platforms come pre-equipped with these safeguards.

In terms of performance, platforms like Salesforce Agentforce show an impressive increase in AI accuracy. For simple tasks, the accuracy jumps from 50% in DIY methods to 95% when using an integrated platform. In more complex tasks—such as sales coaching—accuracy improves from 40% to 95%. This improvement in performance not only accelerates time to value but also boosts the overall efficiency of organizations adopting AI.

Another aspect of agentic AI development is the significant cost and time savings when adopting a pre-integrated platform. As reported by Valoir, businesses using such platforms typically reduce the time spent on development from an average of 75.5 months for DIY approaches to just 4.8 months. This difference in time-to-value could be the deciding factor in the competitive race for AI-driven business transformation.

Fact Checker Results:

• Data Accuracy: Platforms like Salesforce Agentforce provide much higher accuracy rates (up to 95%) for both simple and complex tasks compared to DIY approaches, which have lower success rates.
• Integration Speed: Using deeply integrated AI platforms can reduce setup times by more than 16 times compared to DIY methods.
• Cost Efficiency: While DIY solutions can take up to 12 months to develop trust layers, integrated platforms come with pre-built, trusted solutions that accelerate AI deployment.

References:

Reported By: https://www.zdnet.com/article/how-businesses-are-accelerating-time-to-agentic-ai-value/
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