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From real-time analytics to smarter client matching, companies are using artificial intelligence to turn data into faster, more informed decisions while keeping human judgment at the center.
Artificial intelligence has changed the way businesses make decisions, shifting its role from automating repetitive tasks to helping organizations extract meaningful insights from the data they already possess. Across industries, companies are using AI to identify patterns, anticipate challenges, and respond to changing conditions with greater speed and precision. From retailers managing inventory in real time to legal businesses improving client acquisition, the latest wave of AI adoption reflects a broader move toward data-driven decision-making that combines machine intelligence with human expertise.
AI-Native Analytics Raises the Bar for Business Intelligence
For years, business intelligence platforms promised data-driven decision-making but often required extensive implementation, specialized analysts, and significant licensing costs. This model is now being challenged by AI-native platforms designed to simplify data analysis while improving accuracy.
Genloop, an AI-native analytics platform founded in 2024 by Ayush Gupta, is among the companies seeking to redefine enterprise analytics. Built on a proprietary “living context graph” that continuously learns from an organization’s data estate, the platform achieves 97% accuracy on the Spider 2 benchmark, 22 percentage points ahead of competitors like Snowflake. The results have translated into measurable business outcomes. One mid-market retailer operating 20 stores eliminated its $300,000 annual spending on data consultants while reducing inventory waste by 25% after adopting the platform.
Explaining the company’s approach, Gupta said, “We help organizations work on top of their entire data estate, understand what is happening, proactively tell them the right person, the right thing at the right time, so that they can just take actions.”
While rapid advances in generative AI have made it easier to develop prototypes, Gupta argued that enterprise-grade systems require a much higher standard of performance and governance.
“While AI has made it easy to quickly launch demos and prototypes, the effort to go from 80% accuracy to 95%, closer to 100%, and have systems that are really tending towards perfection and enterprise-grade with governance—that is a completely different challenge. Where our advantage is that we can be completely agile, thinking it from scratch, where incumbents like Power BI have to maintain their complete infrastructures and can only retrofit things that are really not AI native,” he explained.
Beyond cost savings, Gupta believes the greatest value comes from empowering businesses to act on fresh insights instead of relying on historical reporting cycles.
“More than the money they save, it is basically the freedom and the proactiveness they gain. The freedom to see what is happening in my business at an hourly or daily level, and to make decisions at the moment rather than waiting for a quarter—and to optimize my KPIs real-time, that generates a lot more outcomes and a lot more money for them,” he said.
Human Oversight Remains Essential
Even as AI improves the speed and quality of business decisions, industry leaders caution against treating it as a substitute for human judgment. That balance becomes especially important in professions where inaccurate information can have significant financial or legal consequences.
Sameer Somal, CEO of Legal Experts AI, said businesses should view AI as an assistant rather than a decision-maker. His platform focuses on using AI to identify and match the right clients with the right attorneys instead of automating internal legal work, reflecting his belief that growth initiatives should remain the priority.
“You have got to treat artificial intelligence like another associate on your team. And that means you have got to verify their work. Large language models and AI do hallucinate, so it cannot be the end-all, be-all solution. Ultimately, you are accountable,” Somal explained.
He pointed to recent instances in which lawyers were disbarred for submitting AI-generated citations without verification as a reminder that professional responsibility cannot be delegated to technology.
At the same time, Somal argued that AI can strengthen businesses by enhancing, rather than replacing, uniquely human capabilities.
“Artificial intelligence will make smarter people smarter. You have to double, triple down on your ability to connect with others, emotional intelligence, true relationships, and you have to consciously invest time to work on your business, not in your business.”
That philosophy also affects the way Legal Experts AI approaches client acquisition. AI may help identify opportunities, but building trust still depends on people.
“AI will get us an appointment, a phone call, someone interested, but the cognitive framework and your emotional intelligence and the relationship will get that person who is interested in doing business with you to become a client. Fostering trust with them as another human being, and delivering upon that trust, will get you a referral. Get a few referrals and they will get you a community, and building a community will lead to sustainable growth,” Somal said.
Data-Driven Decisions, Powered by People
As businesses continue integrating AI into daily operations, a common pattern is emerging. Organizations generating the greatest value are not replacing human decision-makers but equipping them with faster, more accurate insights. Whether using AI-native analytics to optimize inventory in real time or applying AI to connect legal professionals with prospective clients, success depends on deploying the technology where it delivers measurable value while maintaining human accountability.
