Business success is dependent on having AI-ready data. The way to ensure that is through an iterative process based on the availability of metadata to measure, qualify, and govern the data.
AI is the key to business success. And the keys to AI success are the availability of AI-ready data (which is the result of effective governance and data management practices) and the formulation and prioritized execution of an AI strategy. Even with these things, businesses that reap the most benefits are those that embrace the opportunities of today’s era of collective intelligence to create new value for their organizations.
That’s quite a bit to digest and comprehend. But that, in essence, was the gist of the opening keynote at this week’s Gartner Data & Analytics Summit. The keynote’s theme was “Generating Value Together: From Fundamentals to AI Readiness to Collective Intelligence.” The keynote session was led by Gartner’s Debra Logan, Distinguished VP Analyst, and Ehtisham Zaidi, VP Analyst.
Logan got right to the heart of the matter with her open remarks. “Good morning, and welcome to the era of collective intelligence.” To which Zaidi asked if she could “tell us a bit about collective intelligence.”
To do that, Logan said she’d ask the newest member of their team, Gen AI, what it thought collective intelligence was. Gen AI, as it frequently does, produced a verbose response to the prompt. Logan paraphrased that response, noting:
“Collective intelligence is how we solve problems, how we get things done. It’s the embodiment of that old adage that we all know two heads are better than one and the newer idea of the wisdom of crowds.”
She noted it’s “where communication, collaboration, coordinated action, problem solving, and decision making allow us as living beings to survive, create, and thrive.” She went on to say that human collective intelligence is made powerful with natural language, and natural language is the fundamental feature of our cognition and our communication.
With that said, digital technology has supercharged human collective intelligence by supercharging language. Technology now allows information sharing, communication, and knowledge aggregation to take place at ever-increasing rates.
Leadership must be on board
Collective intelligence requires an assumption that a company understands the fundamental strategic role of data analytics and AI as a core pillar of its foundational strategy. Zaidi noted that the rigorous execution of these fundamentals and a focus on business value can mature a company’s core capabilities.
But he cautioned: “If your executive leadership does not understand the value of D&A maturity, you will not get the support you need to level up. You will be viewed as a cost center and not a value creator.”
Zaidi offered some new Gartner data that data analytics leaders could use to show management the strategic value of data analytics and AI. He said, “Companies in the global S&P 1200 that talked about data analytics and AI being strategic outperformed their peers 80% of the time in the last nine years.”
Logan noted that other Gartner research found similar benefits. Specifically, she noted that Gartner analyzed the data and analytics maturity of over 300 companies against their financial performance and found a 30% difference in net incomes. “The correlation between high levels of D&A and AI maturity and superior financial performance. It’s there. That’s going to get your leadership attention.”
Logan cautioned that once you do get that attention, data and analytics leaders must be prepared to tell those in corporate management exactly how this value is being created.
Zaidi suggested some ways to do this. He pointed out that D&A leaders are focusing on changing culture, creating strategy, embedding D&A initiatives in the business, and managing data governance.
“They’re trying to balance strategy with execution, but fully trying to balance strategy and execution is wrong,” he said. “Those who spend more time on execution-oriented activities such as managing their overall function, delivering on projects, and increasing governance maturity tend to have better financial performance.”
He noted that many of Gartner’s clients are not executing on the governance front. They can’t get governance done because it is difficult and time-consuming, and the business does not see the value, so “you never get the resources.”
He noted that governance is undervalued by both the business and D&A leaders themselves. To change that erroneous perception, he said to emphasize that there is a correlation between high levels of D&A maturity and superior financial performance. There is that 30% increase in a firm’s financial performance, cited earlier in the keynote session.
See also: GenAI: Redefining Data-Driven Transformations
Handling success
Once corporate leaders and business units are convinced of the value of data analytics and AI, there is often an explosion in the demand for AI applications, analytics, and data products.
Logan noted that what often happens is that the D&A leaders have competing priorities. “You need to step up to this. You must lead the AI conversation and execute on governance. Then you will be able to shape the future of your organization.”
To help in this area, Logan introduced the keynote audience to Gartner’s AI Opportunity Radar. The Opportunity Radar is a tool to provide top-down strategic guidance on how AI should support business goals and public and private market perception safely. Essentially, there are two axes. One represents the benefits. Is the project game-changing or aimed at making everyday operations and tasks easier? The other axes is whether the effort is for internal use or applied to clients and customers.
The tool helps strategize different scenarios. For instance, if your ambition is to disrupt your industry with game-changing innovations, that would come with great risk but potentially very high reward. Or a company might want to make incremental improvements to everyday business processes and back office operations using such things as implementing Gen AI, coding assistance, or other productivity assistance capabilities of AI.
Logan cited the work of Rickard Wieselfors, VP and Head of Automation & AI, at Ericsson. Logan noted the company is an example of an AI-first approach. Wieselfors applied AI in all the quadrants of the opportunity radar, and the company managed to realize over $500 million in reported financial benefits.
He used an approach that was 3% strategy and 97% execution. “He has told us the secrets to his success, and they are lead with business value in everything you do. Put in place an end-to-end process built for innovation and scale, and have AI-ready data by creating easy reuse of data assets through data management,” she said.
A final word
To build on that point, Zaidi emphasized that AI-ready data is the result of an iterative process based on the availability of metadata to measure, qualify, and govern the data. To prove data is AI-ready, D&A teams will need to be able to iterate and converge quickly to identify data that is fit for their use.
He closed with the following advice to achieve success: “Establish your enterprise’s AI ambition using our AI opportunity radar to help pilot and scale your D&A projects and revitalize and extend governance to immunize your organization against AI risk.”
Logan noted that a key element to remember is that in this new era of collective intelligence, success is going to be located where organizational purpose meets data and analytics, data and AI literacy, and autonomy. “Your job is to advocate for distributed leadership away from hierarchical decision making, providing data and analytics, access to domain experts as autonomous, trusted decision makers who can see the direct consequences, both good and bad, of their actions,” she said. “Combine data, people, and purpose at the edge to carry out the mission of the organization. Creating value together. This is your moment of truth. We’re actually suggesting that as you mature your D&A function, start with purpose, build a great team, and give them autonomy. You will realize the promise of data and AI.”
