Gartner unveils top four data & analytics trends for 2024
Gartner has identified the top four trends in data and analytics (D&A) for 2024 and discussed their wide-ranging potential challenges, notably organisational and human ones. The power of AI and the rising importance of GenAI are redefining the ways in which people work, collaborate within teams and run processes. Ramke Ramakrishnan, VP Analyst at Gartner, forecasted that "Organisations that fail to make the transition and effectively leverage D&A, in general, and AI, in particular, will not be successful."
The first trend pinpointed is "Betting the Business", indicating that as AI continues to revolutionise industries, D&A leaders are being tasked with drastic AI strategy manoeuvres for enterprises. Ramakrishnan suggested: "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." Gartner foresees that by 2026, chief data and analytics officers (CDAOs) who become trusted partners with CFOs in delivering business value will elevate D&A to a strategic growth driver for organisations.
The second trend, "Managed Complexity", highlights that existing D&A systems are sensitive, and their redundancies can create disorder and additional costs. Ramakrishnan clarified, "Leading organisations are turning this chaos into something they can manage – complexity." To address this complexity effectively, D&A leaders require AI-enabled tools for greater automation and productivity. By 2025, Gartner predicts, CDAOs will have adopted data fabric as a vital factor in successfully addressing data management complexity.
The third trend, "Be Trusted", underscores the issue of data reliability in an era of rapidly advancing GenAI. Ramakrishnan advised that "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." This includes ensuring data is ready for AI, meaning it is secure, ethically governed, bias-free and enriched for accurate responses.
The final trend is the "Empowered Workforce". Organisations are encouraged to invest in developing AI literacy among employees, use adaptive governance practices, and embrace a trust-based approach to managing information assets. Ramakrishnan pointed out, "AI training is not just about quantity; it also requires a different approach. The skill sets required for expert AI users will be very different from other users." Gartner predicts that by 2027, over half of CDAOs will have secured funding for data literacy and AI literacy programs, driven by enterprise failure to realise the expected value from generative AI.
All these trends and their implications will feature prominently at the forthcoming Gartner Data & Analytics Summit, set to take place in Sydney at the end of July. The intention is for IT leaders to integrate these trends into their D&A strategies, opening up avenues of potential growth and innovation for their respective organisations.
