New Delhi, July 3 -- Artificial Intelligence (AI) has become critical for businesses seeking to enhance productivity and elevate performance. While business leaders understand its impact could add trillions of dollars in value to the global economy, they are having challenges to measure Return of Investment (ROI). Moving beyond isolated experiments toward a strategy that delivers measurable value, is critical.
Many organisations stumble by starting with AI projects that are easy to start but deliver little impact. According to recent Mckinsey research, more than 80 percent of respondents say their organisations aren't seeing a tangible impact from their use of GenAI. While these pilots are useful for learning, they fail to generate the measurable outcomes necessary to fund further efforts.
The key to achieving positive results lies in making thoughtful, ROI-driven choices early on. At Dell Technologies, we describe and approach this through the concept of the flywheel effect. In automobiles, the flywheel connects the engine to the drivetrain, allowing the power generated by the engine to be put to work on the road. It's the same with AI projects. They should build on each other, creating a cycle of progress and higher returns.
Understanding the AI Flywheel
The flywheel is about compounding returns. Picture an AI initiative where each successful project delivers ROI and builds a foundation of platforms and supporting infrastructure. This means creating essential systems and tools to operate effectively, like software and hardware. Every rotation of the flywheel represents a step forward, where new initiatives are easier to run, cost less and yield significant gains.
At the heart of this approach is strategic prioritisation. Selecting projects that deliver material gains early on is crucial. For instance, improving a supply chain with AI can uncover millions in savings by increasing efficiency and mitigating risks. For sales teams, AI enhances productivity, providing better insights and tailored recommendations. Ultimately, it results in higher revenue and better engagement with customers.
We've seen these benefits at Dell, where our AI efforts focus on four core areas that drive meaningful impact: sales, services, supply chain and support. These domains represent critical business functions where AI unlocks operational efficiencies and customer value. By targeting high-impact areas first, we've been able to demonstrate ROI, build confidence and secure support for investments.
Picking the Right First Steps
A common mistake in AI adoption is prioritising projects based on ease of implementation. While small-scale pilots may help teams learn new tools or test ideas, they rarely generate business impact. For example, deploying GenAI to improve internal meeting notes might seem helpful, but it's unlikely to shift financial or operational metrics.
Instead, success lies in making calculated choices from the start. Look for areas in your organisation with potential for measurable improvement. Examples include customer-facing services where AI elevates user satisfaction. Or logistics, where predictive analytics can reduce inefficiencies.
Take, for example, the role of AI in customer service. Advanced natural language processing (NLP) models understand user preferences, enabling instant resolutions through virtual agents. Beyond just speed and accuracy, this kind of deployment creates a cascade of benefits, from higher customer satisfaction to reduced costs. These incremental adjustments lead to a bigger return, which fuels the next stage of investment in the flywheel.
The Role of Governance and Infrastructure
While project selection is foundational, the execution phase requires governance and the right infrastructure. For your AI strategy to scale, consistency is critical. Governance frameworks ensure that AI deployments align with business goals and maintain ethical standards. These structures help organisations replicate success instead of starting from scratch with every new initiative.
Creating a technological foundation is also important. Reusable platforms, cloud infrastructure and integrated tools allow teams to carry out projects with reduced time and cost. AI can be resource-intensive but with a solid infrastructure in place, investments become shared assets leading to faster, cheaper and smarter innovation.
We've experienced firsthand how governance and technology lead to improvements. Thanks to an efficient infrastructure and well-defined processes, our AI team has been able to expand efforts across the company. The results speak for themselves. The flywheel runs stronger as systems feed off previous successes, generating increasing ROI with each subsequent step forward.
Visualising Long-Term Success
The goal of an enterprise AI strategy is to create a ROI machine. The effort required to initiate new projects should decrease over time while the gains only grow. Start by focusing on use cases that provide quick wins and set the stage for future opportunities. Make sure to connect your AI initiatives through shared data infrastructure, standardised processes and reusable models. Regularly evaluate progress and provide your teams with the right skills and tools to adapt as your strategy evolves. Keep it simple, scalable and aligned with long-term goals.
The flywheel effect is about purposeful, ROI-driven innovation that empowers organisations to lead in the AI world. Once you target high-value projects, reinforce successes and sustain momentum with strategic governance, AI will become a necessity for long-term business growth. With the right strategy in place, the potential for productivity and transformation is boundless.
Published by HT Digital Content Services with permission from TechCircle.