To truly unlock the transformative power of AI and data, organizations must shift their focus from simply improving existing processes to enabling fundamentally new capabilities and accelerating innovation cycles. Most AI projects focus on productivity improvements, yet without strategic business alignment they fail to produce significant impact. Doing more work faster does not create the AI value most organizations anticipate.

The new imperative is strategic, moving beyond "doing old things faster" to "doing new things smarter." The ability to gain and maintain a competitive advantage now hinges on the speed and agility with which businesses can bring data and AI to life to accelerate and multiply business outcomes. To fully leverage the potential of AI, organizations must operationalize data as a value multiplier, make AI ready data more accessible to their entire ecosystem and use AI to accelerate innovation cycles.

Data is the lifeblood of the enterprise, but only if it can be infused into the business in ways that are transformational. However, infusion is not enough. The speed at which an organization can infuse data into the business directly impacts the speed at which the business can innovate. In turn, the speed of innovation cycles fuels competitive advantage. This kind of agility is only possible with singular data management that enables end-to-end data and AI pipelines. In a unified data engineering platform where raw data is transformed seamlessly into AI ready data, organizations can infuse AI into business processes, create new business models and compete effectively in their markets. (Figure 1.)

Figure 1. The Data to Innovation Value Chain

The ability to securely share and exchange data is paramount to further augmenting an organization's AI agility. Cloud-based data services facilitate data sharing by providing a centralized, secure platform for access by people, applications, devices and AI, all with defined usage policies. Responsible and lawful utilization of data through clear data contracts between providers and consumers, enables data sharing for complex networks of users everywhere.

With data sharing activated across entire business ecosystems, the natural next step is a connected network of AI and AI agents. AI becomes the glue that connects the ecosystem together, allowing it to function as a single organism. AI agents remove the friction that has generally slowed or broken the functioning of the ecosystem at every point where one organization works with another. The combination of AI and AI agents enables the free flow of communication, negotiation, transaction, support and innovation among the enterprise and their suppliers, partners, customers and investors. In the same way we have seen the proliferation of data marketplaces, we will see the emergence of AI marketplaces. (Figure 2.)

Figure 2. The AI and Data Marketplace Ecosystem

Accessibility to AI and AI agents paves the way for the development of new products and services. Forward-looking companies are already transforming their business with new AI-fueled operating models and business models based on concepts never conceived of or never possible apart from a healthy flow of data and AI in an integrated data management platform.

Successful innovation labs operate on four foundational pillars: unified data management, unified AI sharing, business and technical alignment and outcome-based investment. Without any one of these four pillars, AI innovation will fragment to the point where desired outcomes are never achieved.

Four Pillars

ONE: Stop data engineering sprawl and invest in a unified data engineering platform, ideally with a modular, consumption-based pricing model.

TWO: Expand your data strategy beyond the data marketplace to the AI marketplace to fully leverage your technology investments.

THREE: Require every project that enters your innovation lab to have a business sponsor with an ROI model and a technical sponsor with a feasibility analysis.

FOUR: Utilize AI to help you prioritize your AI projects based on your company strategy, ROI, feasibility and time to value.

It all starts with unified data engineering. If you have three or more different data engineering platforms, consolidation to a single platform will make your organization far more AI ready. If you are just starting your data journey, don’t fragment your data engineering, unify. AI readiness will accelerate your innovation cycles beyond the speed of your competition; and you will be the one in your industry to usher in new data economies. The AI tsunami is coming. This is your chance to be the tsunami.

For more information, read the whitepaper, “Shatter the AI Glass Ceiling with Unified Data Management,” featuring expert analysis on Informatica Intelligent Data Management Cloud™ by Ferraro Consulting, LLC.