Organisations Must Navigate Data And Analytics Trends, Leverage AI For Success: Gartner
D&A leaders need to embrace complexity by using AI-enabled tools to automate and improve productivity, it said.
Research and consulting firm Gartner has identified the top data and analytics trends that are driving the emergence of a wide range of challenges, including organisational and human issues. These range from betting the business and managed complexity to empowered workforce.
Gartner suggested that IT leaders must navigate these D&A trends and incorporate it into their D&A strategy.
“The power of AI and the increasing importance of gen AI are changing the way people work, teams collaborate and processes operate,” said Ramke Ramakrishnan, VP analyst at Gartner. “Amidst this technological revolution, organisations that fail to make the transition and effectively leverage D&A, in general, and AI, in particular, will not be successful.”
Below are the D&A trends identified by Gartner:
Betting The Business
As AI continues to impact industries on a strategic level, D&A leaders must demonstrate a bet-the-business skillset on AI and earn trust to lead the AI strategy within the enterprise.
“D&A leaders must demonstrate their value to the organisation by linking the capabilities they are developing and the work they do to achieve the business outcomes required by the organisation,” said Ramakrishnan.
Gartner predicts that by 2026, chief data and analytics officers that become trusted advisors to, and partners with, the CFO in delivering business value will have elevated D&A to a strategic growth driver for the organisation.
Managed Complexity
D&A leaders need to embrace complexity by using AI-enabled tools to automate and improve productivity. This includes investing in augmented data management, decision automation and analytics capabilities like natural language processing.
According to Gartner estimates, by 2025, CDAOs will have adopted data fabric as a driving factor in addressing data management complexity, enabling them to focus on value-adding digital business priorities.
Be Trusted
With the increasing accessibility and efficiency of gen AI, data reliability is constantly being questioned. Lack of trust within organisations, concerns about the value and quality of data, and regulations around AI are leading to a deluge of distrust.
“D&A leaders should use decision intelligence practices to build trust in data and monitor decision-making processes and outcomes. Additionally, implementing effective AI governance and responsible AI practices is crucial in establishing trust among stakeholders. It includes making data AI-ready, which means it is ethically governed, secure and free from bias and is enriched to ensure more accurate responses,” said Ramakrishnan.
Empowered Workforce
It is important that employees feel empowered through the use of AI in D&A, rather than causing them to feel threatened or frustrated by it. Organisations must invest in developing AI literacy among employees, use adaptive governance practices for effective governance, and implement a trust-based approach to managing information assets.
“AI training is not just about quantity; it also requires a different approach. Recognise that the skillsets required for expert AI users will be very different from other users,” said Ramakrishnan.
Gartner estimates that by 2027, more than half of CDAOs will secure funding for data literacy and AI literacy programmes, fuelled by enterprise failure to realise expected value from generative AI.
