AI shifts from support role to core strategy, industries speed up adoption

Global enterprises are moving from routine automation to predictive, real-time intelligence as AI becomes central to operations across sectors

Artificial intelligence has moved from a support function to the core of how companies operate. Enterprise adoption has climbed sharply in the past year. Several global surveys show that more than 70 percent of large organisations have already deployed AI in at least one business unit, and spending on AI systems is expected to cross 300 billion dollars by 2026. The common thread across sectors is a shift from routine automation to real-time, predictive intelligence.

 

Public safety and healthcare agencies are among the earliest beneficiaries of this shift. Emergency departments are using AI to estimate call volumes and predict resource gaps, while hospitals rely on models that scan medical records and vitals to flag patients at risk. These systems now sit on secure cloud platforms that connect data across departments and devices.

 

“AI is changing how public safety and healthcare organizations plan, respond, and care for people. From predicting emergency call volumes to helping doctors spot health risks early, AI is making operations faster, smarter, and more reliable,” said Girish Jambagi, Cloud Security and Public Safety expert at Oracle Corporation USA. He said trust remains essential. “The challenge is to build AI that people can trust — one that keeps information safe, explains its decisions clearly, and supports human judgment.”

 

The same momentum is visible in telecom, finance and consumer-facing sectors, where companies are moving from static dashboards to adaptive intelligence. Models trained on real-time data are guiding credit decisions, improving fraud detection and helping network operators plan capacity. Integrating legacy systems and enforcing governance continue to be major hurdles.

 

“Artificial Intelligence is transforming business strategies across every sector: from finance and telecom to healthcare and manufacturing, by fusing data engineering, BI, and GenAI-driven insights into decision workflows,” said Subhash Tatavarthi, Data Architect at a global telecom network provider. “Success depends on architecting AI ecosystems that are explainable, compliant and scalable.”

 

Manufacturing companies are using AI for design-stage problem solving, quality prediction and supplier evaluation. Studies show that predictive maintenance could save global manufacturers close to a trillion dollars by the end of the decade. In aerospace and defense, AI helps secure sensitive data, detect threats and strengthen mission assurance.

 

“In manufacturing, AI is moving beyond automation and into design-stage intelligence by predicting quality deviations, contextualizing supplier capability, and linking production conformance with reliability data,” said Prashant Kondle, Digital and AI Transformation Leader at Ivis Technologies. He said similar systems support secure collaboration in defense.

 

Energy companies are also leaning on AI to manage grid stability and forecast renewable generation as weather patterns grow unpredictable. Utilities report that intelligent forecasting can reduce outage time and improve planning for solar and wind assets.

 

“Artificial intelligence is no longer a tool in business strategy; it is the strategy,” said Drumil Joshi, Monitoring and Diagnostics Analyst II at Southern Power Company. “Startups and enterprises now achieve in days what once took months, while entire industries shift to predictive, intelligent and self-improving systems.”

 

Retail, banking and education are moving in the same direction. From personalised shopping and automated compliance to adaptive learning and early student-risk detection, AI is reshaping day-to-day operations.

 

“Artificial intelligence is reshaping business strategy across every major sector,” said Nidhi Srivastava, GRC consultant. She noted that AI is accelerating innovation and driving new digital revenue models.

 

Across industries, the message is consistent: organisations that adapt quickly to AI-driven operations will move ahead, while others risk falling behind.