Avtar Sehmbi: Building the AI-First Enterprise Oracle for Banking and Beyond

The AI-First Strategy: Keep it Simple, Create the Oracle

MIAMI, FL / ACCESS Newswire / August 28, 2025 /Avtar Sehmbi, global CxO and member of the Forbes Technology Council and Fast Company Executive Board, believes AI must be viewed not as a tool but as an enterprise oracle: a single, self-evolving system that turns data into foresight, actions into learning, and governance into trust.

"Enterprises don 't need dozens of disconnected pilots-they need a pragmatic path to an AI-first model," Sehmbi explains. "Make the enterprise machine-readable, apply proven analytics where lift is certain, add generative to high-friction steps, and let policy-aware agents carry the work forward under tight controls."

The result, according to Sehmbi, is an enterprise platform that learns, adapts, delivers, and continues to evolve autonomously.

Have Pilots, but Keep Your Eyes on the Big Prize: The Stack
Sehmbi describes the AI stack as a living system, not a set of isolated experiments. "Think of the stack as a production organism," he says, "one that learns across the enterprise, connects signals end-to-end, and adapts in real time for the benefit of the bank."

The fundamentals remain simple:

• Ingestion converts messy enterprise noise into governed signals with lineage.

• Analytics turns those signals into predictions and decisions that directly impact P&L and risk.

• Generative accelerates human tasks-summaries, explanations, code, and content-grounded in trusted data.

• Text-to-picture closes the communication gap by turning language into clear visuals and scenarios.

• Agent chat exposes all of it through safe, goal-oriented assistants that execute, explain, and record.

"Together," Sehmbi notes, "these components shift the enterprise from periodic change to a continuous delivery system."

Imagine Making the Entire Enterprise Machine-Readable - Ingestion
For Sehmbi, every AI win begins with knowing what you have. Ingestion captures documents, calls, chats, screens, orders, and policies, then structures them with metadata, provenance, and access controls.

"The immediate impact is fewer exceptions, faster onboarding, and higher model accuracy because decisions are taken on consistent, traceable data," he explains. Over time, ingestion becomes a shared service feeding feature stores, surveillance, credit models, and agent tools - making new use cases deployable in weeks, not quarters.

Imagine Turning Words Into Decisions in Seconds - Text-to-Picture
"Executives make better choices when complex ideas are shown, not told," Sehmbi says. Text-to-picture systems can translate prompts into pitch-ready charts, dashboards, or storyboards.

He highlights examples: investment bankers iterating client narratives faster, risk teams visualising exposure shifts in seconds, and operations producing training content on demand. Every visual, Sehmbi stresses, must carry its provenance - data source, author, and approval trail.

See Around Corners Before They Appear - Analytics
"Analytics remains the workhorse of enterprise AI," notes Sehmbi. Credit scoring, collections strategy, fraud detection, pricing, and liquidity are domains where measurable lift appears quickly.

"The real value comes not only from sharper models but from treating analytics as a production system-monitored, governed, and continuously improved like any other core business function," he says.

Ship Answers, Not Drafts - Generative
Sehmbi views generative AI as an accelerator for knowledge work when grounded in enterprise truth. "In corporate banking, it drafts coverage notes and diligence summaries; in retail, it personalises offers and scripts; in risk and finance, it explains model outputs. Even in technology, it speeds code conversion and test generation."

The key, he says, is retrieval-augmented design: "Outputs must be anchored to the bank 's data and policies, so the path from prompt to answer is transparent and auditable."

Put a Copilot in Every Workflow - Agent Chat
"Agents are the front door to the stack," Sehmbi explains. A contact-centre copilot resolves intents and executes safe actions. A relationship manager copilot prepares meetings and synthesises notes. An operations copilot clears exceptions by orchestrating document checks and case notes.

"Well-designed agents shorten cycle times, raise first-contact resolution, and leave a complete record for audit and quality assurance," he adds.

Where the Value Lands
Sehmbi outlines where value is already visible:

• Retail & SME Lending: Automating KYC and income verification with ingestion, applying analytics for dynamic pricing, and using generative explainers for compliant customer communication. "The outcome is faster, fairer decisions and fewer abandoned applications," he notes.

• Transaction Banking & Payments: Analytics reduces fraud and false positives, ingestion clears reconciliations, and treasury agents explain fees in plain language. "The result is lower costs and better client satisfaction," says Sehmbi.

• Trade Finance: Heavy documentation can be ingested and verified, analytics spots unusual patterns, and agents coordinate multiple parties. "The payback is fewer manual touches and faster throughput."

• Markets & Investment Banking: Analytics manages pricing, ingestion unifies disclosures, generative assembles pitches, and agents prepare meeting packs. "Producers become more productive while supervision remains consistent," Sehmbi says.

• Financial Crime, Risk & Compliance: Ingestion structures alerts, analytics triages, generative drafts, investigator narratives, and agents shepherd cases. "The outcome is fewer false positives, shorter case times, and stronger regulator confidence."

Create Your Enterprise AI Oracle-Before Your Competition Does
Sehmbi concludes with a clear message:

"Treat AI as your enterprise oracle - a single, self-evolving platform that learns from every interaction and improves itself under clear governance. Build a connected stack on a unified ontology so that value compounds. Early adopters will turn new use cases into assembly rather than invention, while laggards risk being permanently left behind."

About Avtar Sehmbi
Avtar Sehmbi is a global CxO and a member of both the Forbes Technology Council and the Fast Company Executive Board. He advises enterprises worldwide on Tech strategy, digital transformation, and building resilient, future-ready organizations. Follow Avtar on LinkedIn to explore more of his work and insights on driving strategic change in global business.

Media Contact
Avtar Sehmbi
avtarsehmbi@outlook.com

SOURCE:Avtar Sehmbi

View the original press release on ACCESS Newswire

© 2025 ACCESS Newswire. All Rights Reserved.