With CIOs under extreme pressure to enable AI and generative AI (GenAI) capabilities, they’re also scrambling to eliminate data silos. After all, AI needs data—lots of it—and with so much of that data locked in inaccessible silos, AI won’t be as effective.
A recent PWC Pulse survey indicates that about half of CIOs are prioritizing data platform overhauls to provide a unified data platform (pwc.com/us/en/library/pulse-survey/business-reinvention/technology-leaders.html). The solution seems obvious: Break down those silos to enable business growth. With all the data in one place and easily accessible, IT can innovate faster and unearth more insights that will drive revenues and open up new opportunities.
Unfortunately, data transformation initiatives often span multiple years and cost multi-millions in investments, creating tension with the pressing need to leverage AI, particularly GenAI, for immediate competitive advantage. More than 60% of companies surveyed earlier this year by Bain & Company ranked GenAI as one of their top three priorities; 87% were already developing, piloting, or deploying it (bain.com/insights/ai-survey-four-themes-emerging). They fear competitors who deploy GenAI faster than they do will gain competitive advantages that the enterprise may never be able to match. Employees will also apply pressure to adopt GenAI. After all, its rise is creating new expectations among everyday users, following a growing demand for natural language interfaces to consumer AI assistants such as Siri or Alexa. And, of course, enterprise customers have come to expect GenAI capabilities, just like employees.
This presents both an opportunity and a challenge for IT leaders, who must balance rapid deployment of innovative GenAI projects with gargantuan data transformation efforts. It’s a difficult balance for a CIO to achieve. Transforming the data infrastructure while simultaneously implementing cutting-edge AI technologies are two goals that are inevitably at odds with each other.
Given these conflicting priorities, many organizations find themselves caught between two extremes: waiting to deploy GenAI until data transformation is complete (which could take years), or deploying GenAI without full access to enough data to truly repre- sent accurate insights. This struggle often results in prolonged data transformation projects that outlast the tenure of the executives who initiated them, leading to strategy shifts and further delays. All the while, GenAI deployment projects will languish, or, if they do go forward, the lack of easily accessible data will hamstring the AI’s ability to provide accurate insights and sufficient value.
A third way: Leverage AI with advanced BI
With the latest innovations in AI-powered business intelligence (BI), CIOs don’t need to choose between a massive, yearslong data transformation project and fast, efficient deployments of GenAI. A fully modern BI platform can easily integrate data—no matter where it is stored—with AI to deliver convenient, relevant insights to users within their existing apps and workflows.
Modern AI+BI goes beyond the old idea of BI as a series of destination dashboards that data analysts build to visualize heaps of complex data into charts and graphs. Instead, it uses powerful data models combined with no-code web interfaces to deliver bite-sized, contextual intelligence in real time, allowing organizations to reap the benefits traditionally associated with data centralization, but with significantly less disruption, cost, and time investment. With CIOs under extreme pressure to enable AI and generative AI (GenAI) capabilities, they’re also scrambling to eliminate data silos. After all, AI needs data—lots of it—and with so much of that data locked in inaccessible silos, AI won’t be as effective.