Tech Expert Amit Ojha Discusses Why Businesses Must Start with the Problem, Not the 'AI Checkboxing' Trend

As artificial intelligence (AI) triggers the wave of corporate anxiety, organizations race towards integrating it. Unfortunately, this is not out of strategic necessity but out of fear—fear of falling behind competitors, fear of investor scrutiny, and fear of appearing outdated in this era of rapid digital transformation. But as Amit Ojha, a seasoned technology leader, warns, this mindset is leading businesses down the wrong path.

"Too many organizations are asking the wrong question," Ojha explains. "They start with, ‘How can we use AI?' instead of, ‘What problem are we trying to solve?' AI can be a powerful tool, but blindly adopting it for the sake of checking a box is a mistake."

He observes this shift in all industries. Legal teams are using AI to analyze contracts. Developers are using AI-powered tools to write code faster. CFOs are looking at AI-driven operational efficiencies. Every department is being touched by AI in some way. But this underscores the need for leaders to approach AI with a strategic mindset and guide their organizations through this shift.

Ojha, whose expertise spans e-commerce, omnichannel systems, and IoT integration, has built a career helping companies align technology with business objectives. He sees AI as an enabler but only when it's applied with intent. "The goal isn't to have AI. The goal is to improve efficiency, enhance customer experience, or optimize operations. AI, although powerful, is not the right answer to every use case."

In today's landscape, AI capabilities are evolving at breakneck speed. Large language models, autonomous agents, and AI-driven analytics tools are reshaping industries, but many executives remain uncertain about how to proceed. "I have had conversations with leaders across industries, and the recurring theme is uncertainty," Ojha says. "They don't know if AI will change their roles, if their data is ready, if they have the right talent, or how to budget for AI initiatives. And they're being pressured by boards and investors to ‘do something with AI' without a clear long-term strategy."

Rather than succumbing to this pressure, Ojha encourages companies to take a step back. "AI adoption should be fueled by curiosity, not fear. Leaders need to explore AI's potential by asking: ‘Is there a process we can improve? Can AI help us serve better? Can it drive efficiency?' If the answer is yes, then it's worth investigating. But if AI doesn't solve a specific business problem, then it's not the right investment."

Ojha, who has allowed his own curiosity to fuel his long and successful career, understands the excitement behind playing with new technology. But he explains that every AI investment must be tied to a measurable outcome. "Companies often get excited about AI at the start, but by the time they implement it, they realize they've just replaced a $60,000 SaaS tool with a $240,000 AI system and the output is the same spreadsheet," Ojha says. 

Amit Ojha

For AI to deliver real ROI, companies need to start with their end goals. "The right approach isn't ‘Where can we apply AI?' but ‘What outcome are we trying to achieve?'" he emphasizes, further breaking it down, "If your goal is to increase repeat purchase rates, AI can analyze customer behavior and recommend personalized offers. If you want to combat return fraud, AI can detect suspicious patterns in transaction data."

According to Ojha, some industries aren't ready for AI integration. He says, "Many of these businesses are still running on legacy systems. Before they even think about AI, they need to modernize their infrastructure. AI won't fix outdated technology; it needs a solid foundation to be effective." The biggest mistake these companies make, he warns, is assuming AI will automatically lead to better results. "If you train AI on bad data, you get bad predictions. It's garbage in, garbage out. Without a well-defined problem and high-quality data, AI can actually harm your business rather than help it."

On the other hand, he provides a real-world example: "I recently spoke with a content media company that constantly updates financial articles as market data changes. This was a tedious, manual process, so they wanted AI to automate it. That's a great use case. AI can scan articles, identify outdated figures, pull in the latest numbers, and streamline updates. The result? Significant time savings and better content accuracy."

Ultimately, Ojha advises that AI adoption should be driven by curiosity and innovation, not external pressure. "Stop chasing AI just because it's the hot new thing. Take a step back, identify what will truly help your business, and then determine whether AI is the right tool for the job. That's how you move beyond the AI checkbox and toward meaningful innovation."

Image Credit: Amit Ojha

This post was authored by an external contributor and does not represent Benzinga's opinions and has not been edited for content. This content is for informational purposes only and not intended to be investing advice.