Every company is looking for ways to integrate AI, but many plans have yet to return dividends. The key to success: focus on product-alignment and tap the cloud as your backbone. As an example, manufacturers are improving predictive maintenance with AI systems that can watch over vast amounts of data coming in from IoT sensors across the factory.
If you look around, the excitement for AI shows no signs of slowing down. From boardrooms to shop floors, AI has become the centerpiece of the journey toward the autonomous enterprise. According to McKinsey researchers, over the next few years, more than 90% of companies plan to ramp up AI investments. Yet, the reality is sobering. Although most companies are investing in AI, only 1% believe they've reached deployment maturity. Many initiatives remain stuck in pilot limbo, with billions spent but little measurable ROI.
So, why does this gap exist? It’s not because enterprises lack access to advanced algorithms or the right use cases. In fact, they have plenty of both. What’s missing is the ability to scale AI beyond pilots and experiments because most organizations are running AI on outdated infrastructure, using fragmented, project-driven operating models that weren’t designed for the speed that AI demands.
The real answer lies in pairing cloud modernization as the technology backbone with a product-aligned operating model as the organizational enabler. Together, they provide the scale, agility and discipline enterprises need to turn AI from promising prototypes into sustainable, enterprise-wide value.
Two Essential Pillars Of Transformation
The cloud has the elasticity, resilience and global reach required for processing vast data, scaling compute instantly and driving real-time intelligence. According to the Everest Group and HCLTech’s report "Transforming the Core: A Blueprint for AI-powered Mainframe Modernization," many enterprises are combining cloud-first strategies with hybrid modernization, with 40% rearchitecting and 45% replatforming non-core workloads, while 51% are allocating core workloads equally between a mainframe and the cloud to balance reliability with agility. That’s why the cloud is the foundation for the AI-enabled future, making it a strategic imperative.
Through cloud-native platforms, enterprises can gain unified data access that fuels AI models, faster innovation through CI/CD pipelines and built-in security for responsible AI adoption. But although the cloud provides the foundation, the way organizations are structured determines whether they can build effectively. Traditional project-led models are designed for short-term deliverables with sequential handoffs. This creates silos, making such structures misaligned with modern cloud-native capabilities.
This is where the product-aligned operating model comes in. By organizing cross-functional teams around products and outcomes, this model helps ensure that cloud-enabled capabilities translate into business value. It breaks down silos, embeds feedback loops and allows AI solutions to be iterated, tested and deployed at pace.
Here’s how: Cross-functional teams work as unified units with direct customer input, enabling continuous testing, refinement and deployment rather than slow release cycles. Our research shows that organizations with a product-aligned model are four times more likely to maximize ROI on AI investments. And Everest Group reported that pioneers of this approach are now seeing nearly two times stronger strategic and operational performance.
In essence, cloud modernization and product-aligned teams form two interdependent pillars, building a scalable, AI-ready foundation, driving sustained innovation and delivering measurable returns. Modernization also generates long-term financial benefits, with Everest Group noting that enterprises can achieve significant cost efficiencies while enabling innovation.
The Result Is Enterprise AI At Scale
By combining the cloud with a product-aligned operating model, organizations can move AI out of pilot mode and into business-critical operations. This means intelligence embedded directly into products, services and workflows, enabling faster decisions and new avenues of growth. More importantly, it allows customers, employees and partners to benefit from seamless, connected and context-aware interactions. This is the foundation for experience-led transformation that helps ensure that AI delivers value across the ecosystem.
With cloud-native data platforms and product-aligned teams, banks are taking AI-powered fraud detection and risk modeling beyond experimentation by deploying models that are continuously refined and scaled. This means up to a 40% reduction in false positives and stronger compliance.
In life sciences, the cloud provides the infrastructure to process massive genomic datasets. Cross-functional teams of researchers, data scientists and clinicians can iterate rapidly on AI-driven models, leading to faster trials, more precise therapies and quicker time-to-market for treatments.
Manufacturers are embedding AI into production lines to enable predictive maintenance and improve quality. By pairing cloud-based IoT data streams with product-aligned teams, organizations are testing, deploying and refining AI models that deliver up to 20% improvements in output, 20% increase in productivity and 15% more capacity.
Looking Ahead
In 2023, generative AI started dominating the enterprise discourse, creating significant adoption growth. This has driven demand for massive compute, scalable data pipelines and continuous fine-tuning. But this is only the beginning. The next wave will bring AI agents that can reason, act and collaborate across complex workflows. According to a recent Barclays report, the AI agent era is already here, with widespread use expected by 2026. Rising usage, combined with falling compute costs, means infrastructure and operational demands are set to grow dramatically. But without the right technology foundation and supporting operating model, it will be impossible to keep pace.
The focus must now shift toward turning AI investments into real ROI. As the technology continues to evolve, the groundwork laid today with cloud modernization and a product-aligned operating model will determine who can move fastest and safest in this new paradigm.
This article was written by Sadagopan S from Forbes and was legally licensed through the DiveMarketplace by Industry Dive. Please direct all licensing questions to legal@industrydive.com.
