Top trends to watch in the new year include shifting AI strategies, growing data democratization initiatives and evolving C-suite roles
Nuremberg – December 14 – Exasol, the high-performance Loading...analytics database provider, today released its forward-looking annual predictions for the data analytics space in 2024. As disruptive technologies like Loading...artificial intelligence (AI) continue to make their mark in the tech industry, data-driven companies are faced with navigating new challenges around automation, data silos, ethics, FinOps and evolving C-suite roles in order to meet new data analytics demands. Exasol’s top trends to watch in these areas for the year ahead include:
Prediction #1: AI shifts from reactionary to intentional, unlocking opportunity while eliminating data collection-based roles
In 2023, we saw knee-jerk reactions to AI, leading to poorly designed and executed automation experiments from organizations. In 2024, AI will shift from reactionary to strategic, resulting in more business benefit-driven use cases leveraging AI and Loading...machine learning (ML).
As AI is paired with more technologies, like open source, we will see new models emerge to solve traditional business problems. Generative AI, like ChatGPT, will also merge with more traditional AI technology to open new opportunities for organizations and streamline processes. As a result, AI will continue to eliminate redundant job roles that involve high levels of repetition, data collection and data processing, with customer service, retail sales, manufacturing production and office support expected to be most impacted by the end of 2024.
Prediction #2: Data silos come crashing down as data democratization finally happens, creating a need to train the workforce on insights-driven skill sets
In 2024, more people across various departments will finally have access to meaningful insights through data democratization initiatives, alleviating bottlenecks caused by data analytics teams. Without these silos, organizations will realize the even greater need for their teams and individuals to utilize data in their work, including those who don’t currently consider themselves a data end user. With this shift, the workforce will also need to be upgraded in order for every employee to gain the proper skill set to effectively use data and insights to make business decisions.
Prediction #3: Expect AI backlash, as organizations waste more time and money trying to ‘get it right’
AI experimentation will be a key theme for many organizations in the first half of 2024. Those responsible for AI implementation must lead with a mindset of “try fast, fail fast,” but the most successful organizations will fail fast and quickly rebound from lessons learned. Enterprises should anticipate spending extra time and money on AI experimentation, given that most of these practices are not rooted in a scientific approach. With failure will also come greater questioning around the data fueling AI’s potential, including whether or not clean data is being used, and the legal rights and ethics around the data. With any new technology comes greater questioning, and in turn, more involvement across the entire enterprise.
Prediction #4: FinOps becomes a business priority, as CIOs analyze price/performance across the tech stack
In 2024, we will see FinOps practice the financial governance of cloud IT operations as organizations attempt to prevent unpredictable and chaotic cloud spend and gain assurance from the CIO that cloud investments are aligned with business objectives. As IT budgetary headwinds prevail, the ability to save on cloud spend represents a real opportunity for cost optimization for the CIO. One of the most important metrics for achieving this goal will be price/performance, as it provides a comparative gauge of resource efficiency in the data tech stack.
Prediction #5: AI governance becomes a C-level imperative, causing CDOs to reach their breaking point
The practice of AI governance will become a C-level imperative in 2024 as businesses seek to leverage the game-changing opportunities it presents while balancing responsible and compliant use, especially with the emergence of generative AI.
While AI governance requires collaboration across data teams, the responsibility squarely rests on CDOs’ shoulders. The introduction of new AI regulations and evolving regulatory landscape will push certain CDOs to their breaking point. For others, it will underscore the importance of establishing a fully-resourced AI governance capability, coupled with C-level oversight. This strategic approach not only addresses immediate challenges, but also strengthens the overall case for proactive and well-supported AI governance going forward.
“Organizations face many challenges in today’s rapidly evolving tech landscape. From disruptive technologies like AI to downward pressure on IT budgets and ever-evolving regulations, it’s no easy task to be a data-driven company that remains fully optimized and compliant,” said Helena Schwenk, VP, Chief Data & Analytics Office, Exasol. “As we head into 2024, it’s more important than ever for organizations to invest in the right tools that enable them to stay agile, boost performance and accelerate insights while keeping costs and compliance in check. We all must learn how to harness the full potential of our data in this environment, or risk falling behind the competition.”
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