Industry executives and experts share their predictions for 2024.  Read them in this 16th annual VMblog.com series exclusive.

Insight from 4 Experts on Data, AI, and the C-Suite

By John Knieriemen, Exasol General Manager, North America

2023 was a record year for technological advancements, especially in the artificial intelligence (AI) space, as the world watched generative AI take center stage for many tech-focused organizations. It was a year of growth, learning, and pushing the boundaries with little sign of slowing down. It is no wonder that, when I asked my colleagues at Exasol about what they expect 2024 to bring, the majority of them focused on the future of AI.

But as AI continues to make its mark, we're also seeing data-driven companies navigate challenges around data silos, FinOps, evolving C-suite roles, and more. Let's take a look:

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Mathias Golombek, CTO:

AI shifts from reactionary to intentional, unlocking opportunity while eliminating data collection-based roles

The year 2023 introduced AI, which caused knee-jerk reactions from organizations that ultimately spawned countless poorly designed and executed automation experiments. In 2024, AI will shift from reactionary to strategic, rooted in purposeful proofs of concept that bring more clarity and focus on business objectives. We'll see more business benefit-driven use cases leveraging AI and ML than ever before.

As AI is paired with other technologies, like open source, we'll see new models emerge to solve traditional business problems. Generative AI, like ChatGPT, will also merge with more traditional AI technology, such as descriptive or predictive analytics, to open new opportunities for organizations and streamline traditionally cumbersome 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.

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Florian Wenzel, Global Head of Solution Engineering:

Expect AI backlash, as organizations waste more time and money trying to ‘get it right'

As organizations dive deeper into AI, experimentation is bound to be a key theme in the first half of 2024. Those responsible for AI implementation must lead with a mindset of "try fast, fail fast." But too often, these roles do not understand the variables they are targeting, do not have clear expected outcomes, and struggle to ask the right questions of AI. 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. At the end of the year, clear winners of AI will emerge if the right conclusions are drawn.

With failure also comes greater questioning around the data fueling AI's potential. For example, data analysts and C-suite leaders will both raise questions such as: How clean is the data we're using? What's our legal right to this data, specifically if used in any new models? What about our customers' legal rights? With any new technology comes greater questioning, and in turn, more involvement across the entire enterprise.

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Helena Schwenk, VP, Chief Data & Analytics Officer:

AI governance becomes C-level imperative, causing CDOs to reach their breaking point

The practice of AI governance will become a C-level imperative as businesses seek to leverage the game-changing opportunities it presents while balancing responsible and compliant use. This challenge is further emphasized by the emergence of generative AI, adding complexity to the landscape.

AI governance is a collective effort, demanding collaborative efforts across functions to address the ethical, legal, social, and operational implications of AI. Nonetheless, for CDOs, the responsibility squarely rests on their shoulders. The impending introduction of new AI regulations adds an additional layer of complexity, as CDOs grapple with an evolving regulatory landscape that threatens substantial fines for non-compliance, potentially costing millions.

This pressure 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 strengthens the overall case for proactive and well-supported AI governance going forward.

FinOps becomes a business priority, as CIOs analyze price / performance across the tech stack

Last year, we predicted that CFOs would become more cloud-savvy amidst recession fears, and we watched this unfold as organizations shifted to a "do more with less" mentality. In 2024, FinOps practices the financial governance of cloud IT operations, as the business takes aim at preventing unpredictable, sometimes chaotic, cloud spend and gains 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 is price/performance, as it provides a comparative gauge of resource efficiency in the data tech stack. Given most FinOps practices are immature, we expect CIOs to spearhead these efforts and start to perform regular price/performance reviews.

FinOps will become even more important against the backdrop of organizations reporting on ESG and sustainability initiatives. Beyond its role in forecasting, monitoring, and optimizing resource usage, FinOps practices will become more integral to driving carbon efficiencies to align with the sustainability goals of the organization.

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Chad Thompson, CMO

Data silos come crashing down as data democratization finally happens, creating a need to train the workforce on insights-driven skill sets

The year 2024 is when data democratization will shift from a topic of discussion to action within organizations. More people, across various departments, will finally have access to meaningful insights, alleviating the traditional bottlenecks caused by data analytics teams. As these traditional silos come crashing down, organizations will realize just how wide and deep the need is for their teams and individuals to use data. Even people who don't currently think they are an end user of data will be pulled into feed off of data, with 2024 being the catalyst for such change.

With this shift comes a major challenge to anticipate in the coming years -- the workforce will 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. Today's workforce won't know the right questions to ask of its data feed, or the automation powering it. The value of being able to articulate precise, probing and business-tethered questions just increased in value, creating a dire need to train the workforce on this capability.

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While no one can be certain of what the future holds in the technology industry, history has shown us that this sector will continue to forge its own path ahead. We have an exciting year ahead, and I look forward to seeing how some of these trends will play out in the coming months.

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ABOUT THE AUTHOR

John Knieriemen joined Exasol in 2022 as leader of the North America business, with responsibility for strategically scaling business presence across industries and expanding the organization's partner network. John has more than two decades of data and analytics experience, with deep expertise in new logo acquisition, account management, and solutioning in the data warehousing, big data, and cloud analytics space. Before joining Exasol, John served as vice president and general manager at Teradata, spending over 11 years in senior management roles. John holds a Bachelor's degree in Computer Engineering from Texas A&M University.