Where Agentic AI Fits In Business Strategy

Imran Aftab, CEO and Cofounder, 10Pearls—driving AI innovation and creating meaningful opportunities that make an impact.

Economic volatility is inevitable, and when downturns happen, unprepared businesses often scramble to regain their footing.

In 2025, as businesses again feel the brunt of economic turbulence, only a third of business leaders express high confidence in their company’s growth. Times like these challenge long-standing definitions of agility for business leaders.

Technology is at the heart of reshaping the new definition of agility, and advanced solutions like agentic AI are poised to power this transformation.

To stay ahead, businesses will need to invest more in technology, regardless of industry. They must reimagine and digitize operations and processes to achieve a competitive edge, remain resilient, and adeptly navigate uncertainty now and in the near future.

What’s At Stake For Businesses

Many businesses face operational risks due to rigid workflows and a lack of agility. With workflows that fail to adapt quickly to changing circumstances or weak data infrastructures plagued by silos, the result is often slower action and decision making.

These risks are exacerbated by ongoing technology gaps where businesses lack the solutions needed to progress. Outdated legacy systems and accumulated technical debt also drain resources, with businesses spending an average of nearly $3 million on technology upgrades.

Such problems ultimately put businesses at a competitive disadvantage and financial risk, not to mention reputational damage if their ability to service customers is undermined.

Agentic AI’s Role In Building Agility

Agentic AI solutions are autonomous tools capable of making intelligent decisions and learning in real time from their environments without human input. Agentic AI is enhancing operational efficiency while reducing costs associated with unproductive workflows.

They also contribute to predictive maintenance and scalability, helping organizations run machines for longer and scale without proportional resource expansion. For instance, leaders might enable remote diagnostics of a device or machine and automate the ordering of replacement parts via AI agents, minimizing manual intervention as the number of monitored assets grows.

Additionally, agentic AI’s constant analysis of massive datasets enables businesses to adjust dynamically in real time to market shifts, supply chain disruptions or changing customer demands.

The Starting Point For Adopting Agentic AI

Before integrating agentic AI tools into existing pipelines and IT infrastructures, businesses must establish a solid blueprint. Without this, they risk failure and crashing before even taking off.

The first step is determining how agentic AI aligns with business objectives. What are the company’s biggest bottlenecks, and how can agentic AI address these? Identifying resource constraints, process delays and high operational costs, as well as pinpointing repetitive processes suitable for automation, will provide quick wins.

Strengthening Data Infrastructure

Good data is a key pillar for successfully adopting agentic AI tools—and AI solutions in general.

However, “good” data must be clean, accurate, shareable and secure. Preparing training data is non-negotiable since these tools rely entirely on their data and information environments. This could involve cleaning up data for specific use cases, like using real-life data from previous customer interactions to train AI agents for customer care relations.

High-quality, frequently updated data empowers businesses to be more agile, keeping a close pulse on operations and workflows and continuously identifying improvement opportunities.

Ensuring Compliance

Compliance is essential to optimal AI performance, including mitigating bias and ensuring tool security. Unreliable AI agents can be biased and make poor decisions, defeating the purpose of adopting the technology.

In terms of data privacy, organizations must comply with data protection regulations like the EU’s General Data Protection Regulation to avoid vulnerabilities to cyberattacks, which can undermine resilience and agility.

Adopting A Growth Mindset

Agility requires embracing change and adopting a growth mindset from a top-down approach. This helps organizations tackle challenges that lead to bottlenecks when integrating new technologies like agentic AI.

Leaders can set the tone by listening to fresh experiences and expert voices to stay ahead of rapidly changing circumstances and truly understand how agentic AI can assist.

Technical teams involved in AI development could enhance broader skills, such as design thinking and problem-solving. These softer skills make them more adept at intervening when necessary.

Other teams less familiar with AI also benefit from a growth mindset to maximize agentic AI’s presence in business workflows. Hands-on training with real-world scenarios is an effective way to build technology confidence among employees. Organizations can also implement reward programs to incentivize teams to adopt an innovation-first, continuous learning approach to AI.

Agility now means staying abreast of rapidly evolving technologies and being able to quickly shift gears when market factors change. Agentic AI tools have the potential to streamline processes, make workflows more efficient and flexible and free up teams’ time to focus on more strategic and creative areas of the business. However, they can only achieve so much without the driving force of an organization-wide growth mindset.

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