Why Many Businesses Aren't Seeing ROI from AI and How To Fix That

Article summary: 

• Many businesses are using generative AI but aren't seeing significant bottom-line impact, creating a "Gen AI Paradox."
• First-generation GenAI's limitations, like being reactive and struggling with complexity, have hindered its ability to deliver substantial ROI.
• Agentic AI is the game-changer, enabling autonomous, goal-driven execution and automating complex workflows to unlock real ROI and transform business operations.

Here's a head-scratcher: nearly eight in ten companies are reportedly using generative AI (GenAI). That's a huge adoption rate! But here's the kicker – just as many report no significant bottom-line impact. What gives? It’s what we call the "Gen AI Paradox," and if you've been dabbling with GenAI without seeing huge returns, you're not alone. The good news is, there's a powerful way to shift from experimentation to actual payoff, and it involves getting cozy with agentic AI.

Here at SalesApe, we're all about empowering businesses with powerful compute capabilities previously only available for big tech. It’s time to drive productivity to new heights and free your people to do what we humans do best: forging real-world connections and adding value where it truly matters.

The Gen AI Paradox, Its Widespread Use & Minimal Impact

When tools like ChatGPT burst onto the scene in late 2022, they democratized access to advanced AI like never before. It felt like everyone was experimenting, and for good reason! Generative AI excels at producing content based on direct, specific prompts. Think high-quality initial drafts of documents, quick summaries of large information volumes, or transforming technical language into plain English. These "horizontal" use cases, like enterprise-wide copilots and chatbots, have scaled quickly. 

Did you know…

Nearly 70% of Fortune companies use Microsoft 365 Copilot.

Source

And while these tools enhance individual productivity by helping employees save time on routine tasks and access information more efficiently, the improvements tend to be spread thinly across employees. As a result, they're "not easily visible in terms of top- or bottom-line results". More than 80% of companies still report no material contribution to earnings from their GenAI initiatives. Only 1% of enterprises view their GenAI strategies as mature. It's a paradox: lots of energy, investment, and potential, but at-scale impact has yet to materialize for most organizations.

Why Gen AI Hasn't Fully Delivered (Yet)

The limited bottom-line impact of GenAI in many cases can be attributed to a few key factors:

• Reactive and Isolated: First-generation LLMs are fundamentally passive; they don't act unless prompted and can't independently drive workflows or make decisions without human initiation. They're typically request-response models
• Struggles with Complexity: LLMs have struggled to handle complex workflows involving multiple steps, decision points, or branching logic
• Limited Memory: Many current LLMs have limited persistent memory, making it difficult to track context over time or operate coherently across extended interactions
• Narrow Gains: Most GenAI initiatives focused on plugging a solution into a specific step of an existing process. This delivered narrow gains without changing the overall structure of how work is done, limiting their impact on business performance.

Agentic AI Is The Key to Unlocking Real ROI

This is where agentic AI swings in to break the paradox. Agentic AI marks a major evolution, extending generative AI from reactive content generation to autonomous, goal-driven execution. These systems can:

• Understand goals
• Break them into subtasks
• Interact with both humans and other systems
• Execute actions
• Adapt in real-time. 

All with minimal human intervention. They combine LLMs with components that provide memory, planning, orchestration, and integration.

The real breakthrough comes in the "vertical realm" – use cases embedded into specific business functions and processes. Agentic AI enables the automation of complex business workflows involving multiple steps, actors, and systems – processes that were previously beyond the capabilities of first-generation GenAI tools.

Agentic AI delivers more than just efficiency; it supercharges operational agility and unlocks new revenue opportunities. It transforms processes by:

• Accelerating Execution: Eliminates delays and enables parallel processing, reducing cycle time and boosting responsiveness
• Bringing Adaptability: Continuously ingests data and adjusts process flows on the fly, flagging anomalies before they cascade into failures
• Enabling Personalization: Dynamically tailors interactions and decisions to individual customer profiles or behaviors
• Providing Elasticity: Execution capacity can expand or contract in real-time based on workload or unexpected surges
• Increasing Resilience: Monitors disruptions, reroutes operations, and escalates only when needed, keeping processes running.

Examples of Agentic Impact

Companies are already seeing significant, measurable returns:

Banking Modernization: 

One large bank used a "hybrid digital factory" with AI agents overseeing tasks in software modernization. Human workers moved to supervisory roles, and the impact was a "more than 50% reduction in time and effort in the early adopter teams". Source

Credit-Risk Memo Reinvention: 

A retail bank reimagined its credit-risk memo creation with AI agents. This shifted the analyst's role from manual drafting to strategic oversight. The impact? A "potential 20 to 60 percent increase in productivity, including a 30 percent improvement in credit turnaround". Source

Data Quality Boost: 

A market research firm deployed a multi-agent solution that autonomously identifies data anomalies and explains shifts in sales or market share. While not yet in production, it's demonstrated "more than 60 percent potential productivity gain and expected savings of more than $3 million annually". Source

Automated Customer Service Desk: 

In a reimagined call center, AI agents proactively detect common customer issues, diagnose them, initiate resolution steps automatically, and communicate directly with customers. This could lead to a "radical improvement of customer service desk productivity" with "up to 80 percent of common incidents resolved autonomously, with a reduction in time to resolution of 60 to 90 percent". Source

For your business, this means moving beyond simple AI experiments to truly transforming core processes. Solutions like SalesApe, with its agentic AI for inbound lead qualification, directly contribute to the bottom line by saving your sales team valuable time and maximizing conversion. It's about getting real, measurable results where it counts.

Moving Beyond Experimentation

The first wave of GenAI wasn't wasted; it built awareness and allowed for broad experimentation. But realizing the full promise of agentic AI requires a shift in design mindset – from simply automating tasks within an existing process to reinventing the entire process with human and agentic coworkers. This pivot cannot be delegated; it must be initiated and led by executives.

Agentic AI isn't an incremental step; it is the foundation of the next-generation operating model. CEOs who act now won't just gain a performance edge; they will redefine how their organizations think, decide, and execute. The time for exploration is ending. The time for transformation is now. It's time to move from paradox to undeniable payoff.

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