How Augmented AI Turns AI Strategy Into Business Results with Amar Lingam

Spotlight Interview: Amar Lingam on Turning AI Strategy Into Business Results

In this Technology Executives Club® Spotlight Interview, Alex Jarett sits down with Amar Lingam, Founder of Augmented AI, former Chief Analytics and AI Officer at CDW, and former Chief Data Officer at CA Technologies, to discuss how organizations can move from AI ideas and technology investments to measurable business results. 

With more than three decades of experience leading major data, analytics, AI, and digital transformation initiatives, Amar brings the perspective of someone who has worked inside large global organizations and understands the challenges technology executives face.

Throughout the conversation, Amar emphasizes that successful AI initiatives must begin with the business problem, not the technology.

Be a Businessperson First

One of Amar’s biggest lessons from leading enterprise transformation programs is the importance of being a businessperson first, even when you are a technologist at heart.

Organizations may invest millions of dollars in software, data platforms, and AI capabilities, but those investments only create value when they lead to better decisions, improved operations, or measurable business outcomes.

Amar explains that individual business units are often working hard to improve their own areas. The challenge is bringing those priorities together into a shared enterprise vision.

From AI Strategy to Execution

Amar founded Augmented AI after seeing a gap in the market for partners who could help technology leaders shape their vision and then help them execute it.

Many consulting organizations focus on strategy without implementation. Others focus on implementation without fully understanding the broader business objectives.

Augmented AI works across the full lifecycle, including strategy, roadmap development, business case creation, implementation, and ongoing operations.

Amar describes working with executive, business, and technology stakeholders to understand the organization’s goals, identify high-value opportunities, prioritize use cases, and determine the right technology approach.

Creating Operational Results for a Utility Company

One example Amar shares involves a utility company that wanted to improve maintenance operations and gain better visibility into what was happening across its field infrastructure.

The company had large amounts of data coming from utility lines, field operations, inspections, and equipment, but it lacked a clear way to bring that information together and use it to improve decisions.

Amar and his team began by developing an AI and technology strategy aligned with the company’s broader business goals. They brought together executive leaders, technology teams, and business stakeholders for a two-day workshop to identify challenges, prioritize opportunities, and create a roadmap.

The team then moved into quick wins, proof-of-concept projects, and milestone-based implementation.

The project gave the company better visibility into its field operations and helped it improve preventive maintenance, inspection scheduling, and the use of field personnel.

According to Amar, the company achieved operational efficiency improvements of more than 50% in some areas, reduced scheduling inefficiencies by approximately 20% to 25%, and generated millions of dollars in strategic value.

Turning Digital Assets Into Usable Intelligence

Amar also discusses AssetIQ, an Augmented AI solution designed to help organizations find, understand, and use large collections of digital assets.

The idea originated with a retail company that had years of videos, images, advertisements, and marketing materials stored across a large media archive.

The company wanted to reuse older content for a new campaign, but finding the right footage required searching through enormous volumes of material with limited metadata.

AssetIQ uses AI to analyze digital assets, generate metadata, and create an enterprise search layer that allows users to search for content based on subjects, products, celebrities, sports, weather conditions, campaign themes, and other characteristics.

Instead of treating the assets as a passive archive, the organization can turn them into an active source of business intelligence.

Improving Marketing Campaign Performance

In another retail example, AssetIQ helped a company analyze which advertisements and creative assets had performed well with specific audience segments.

The company could identify the themes and content that resonated with those audiences and use those insights to create more targeted marketing campaigns.

Amar explains that the value is not simply finding an old image or video. The intelligence layer helps organizations understand how assets were used, which audiences they reached, and which content produced better results.

The success of the initial use case also opened the door to additional applications across the organization.

Supporting Healthcare Decisions with AI

Amar also shares a healthcare application involving medical images such as X-rays, CT scans, and MRIs.

The solution analyzes images and compares them with established medical benchmarks related to specific conditions. It can then provide insights and recommendations that support radiologists and physicians as they evaluate the results.

The goal is to help healthcare professionals use their limited time more efficiently and accelerate the analysis and decision-making process.

Amar emphasizes that the AI does not replace the healthcare professional. The technology augments the process with additional intelligence, while physicians and radiologists remain the final decision-makers.

➡️ Watch the full Spotlight Interview with Amar Lingam to hear how Augmented AI helps organizations move from AI strategy to implementation, measurable business outcomes, and more productive use of their digital assets.

*️⃣ Guest: Amar Lingam, Founder, Augmented AI

*️⃣ Host: ALEX JARETT, Founder, Technology Executives Club®