AI’s Impact on Data Sovereignty, Quality, Ethics and Analytics: C-Suite execs from Reltio and Teradata share their perspective
We spoke to C-Suite execs at master data management leader Reltio and global data analytics platform provider Teradata on how they think AI will continue to impact their industries and society more broadly, as we head into 2024
Manish Sood, CEO at Reltio
As boardrooms and C-suites intensify their focus on AI, the spotlight will magnify the imperative to resolve underlying data issues.
In 2024, more CEOs and boardrooms will increasingly realise that data is the linchpin for AI’s success. I’m witnessing a seismic shift in the executive mindset; for the first time in years, CEOs actively seek to increase their technology spend, particularly in AI, as they see great promise. CEOs are not merely intrigued by AI’s potential; they’re captivated by the promise of GenAI to redefine the very fabric of how we conduct business—from revolutionising customer experiences to optimising supply chains and bolstering risk management.
The allure of AI is undeniable; it holds the key to unlocking new markets, saving millions, and catapulting companies into a league of their own. However, the sobering truth that every CIO understands is that AI is not a plug-and-play miracle. The Achilles’ heel lies within our data—the most valuable yet underperforming asset due to its fragmented nature. Investments in AI are futile without unifying and managing our data to ensure it’s clean, connected, and trustworthy. The path to AI’s promise is paved with data unification. It’s about transforming data into a singular, interoperable product that can truly catalyse digital transformation and harness AI’s transformative power.
The triple threat of data sovereignty, privacy, and security is heightened by the age of AI/ML and rapidly transforming how we protect, govern, and leverage information.
In an era where the digital frontier is continually expanding, the spectre of cyber threats looms larger than ever, casting a shadow on the sanctity of data sovereignty, privacy, and security. I see a pressing imperative for enterprises to fortify their defences against this relentless tide of risks, breaches, and ever-tightening global regulations. The age of AI has magnified these concerns, necessitating a robust shield for our most valuable asset: data.
Leveraging data unification and management solutions, which are inherently flexible and scalable, is not just a strategic move—it’s a cornerstone for ensuring compliance and securing the bastions of our digital identities. These tools are the vanguards that can help us navigate the complex labyrinth of security risks and regulatory demands, ensuring that our data remains inviolable and sovereign.
The need for reusable data will drive the adoption of data management and unification tools integrated with AI/ML capabilities.
We’re on the cusp of a data renaissance where sophisticated data management and unification tools, seamlessly integrated with AI and ML capabilities, will enhance and revolutionise how we automate and deliver data products. This is about crafting certified, effortlessly consumable, and eminently reusable data assets tailored to many business use cases. We’re not just talking about making data work smarter; we’re architecting a future where data becomes the lifeblood of decision-making and operations, driving unprecedented efficiency and innovation across industries.”
As GenAI propels us into an era of conversational applications, its success will be unequivocally tied to data quality.
The future of applications will be conversational.. hinge on their ability to access, interpret, and learn from clean, structured, and rich datasets. The most transformative applications will be those that are not just data-driven but data-intelligent—capable of refining their algorithms through continuous data assimilation, ensuring ever-increasing accuracy and relevance in a dynamically changing world.
Steve McMillan, CEO and President at Teradata
AI projects will be judged on their ability to be truly transformative & novel
In 2023, enterprises latched onto the ChatGPT and large language model (LLM) AI craze. In 2024, expect to see AI truly enabling the era of creativity in which technology will be fundamental in transforming industries. There will be a strong shift to investments in generative AI programs that will be revolutionary (rather than simply novel) and deliver better outcomes. The focus going forward will be on generating solutions that improve the efficiency and effectiveness of internal operations by embedding AI into the organisations’ products and services wherever it makes sense.
Doing this well means ensuring the data for AI projects is clean, accurate and trustworthy. As more organisations leverage AI-driven automation and integrate AI and machine learning (ML) into nearly every aspect of their business decision-making, getting the data right will not be a “nice to have,” but rather an “absolutely must have.”
2024 will be the year of AI experimentation and discovery
As more and more organisations need to unleash data, and open data in particular, the demand for solutions that enable AI exploration and discovery at enterprise scale will grow dramatically in 2024. Emerging options that include serverless query engines that spin up in the cloud with powerful analytics, integrate data with advanced LLMs, and access multiple open table formats in high performance will best address the experimentation needs of enterprises. That’s because they will make it easier for data scientists, data engineers, and developers to explore and discover innovative new use cases — on-demand and using data at scale. Expect to see much more enterprise value and breakthrough business results being operationalised with AI thanks to solutions like these.
Trusted AI, Ethics, and Sustainability
In 2024. It will become increasingly apparent that AI must be trusted, ethical and sustainable. Everyone will be talking about trusted information and trust in information. This is important because without knowing and trusting the data sets used for AI projects, can you really be comfortable with the outputs? The quality of predictions or insights is only as good as the data that informs it. In the coming months, the inception point for AI projects should always start with this: “Can you trust the data? Is it clean and reliable?”
We’ll also see more scrutiny around data ethics. Governments worldwide are calling for greater accountability and transparency with AI, particularly around the data used in training AI systems. Similarly, consumers can and will demand greater visibility into how data is used by AI in decision-making that may impact them for transactions like mortgage loans or insurance policies. To address these issues, more companies will develop AI/ML approval processes that include review by an ethics committee. We’ll see more implementations of ethics measures, including monitoring for bias and fairness in AI/ML models and data over time.
Finally, we’ll also see more companies thoroughly scrutinising and addressing the impact of the immense energy usage of AI. Much of this will revolve around having efficient AI models. That will bring about a rise in small and medium language models that can be customised for certain AI applications, while also being accurate, secure and potentially more efficient.
Hillary Ashton, Chief Product Officer at Teradata
Focus will shift from early AI excitement to GenAI productivity and ethics
2023 was defined by the rapid rise of ChatGPT. Next year, the focus on AI will shift from eagerness and excitement around large language model AI to what’s next. First, I foresee a massive productivity leap forward through GenAI, especially in technology and software. It’s getting more cost effective to get into GenAI, and there are lots more solutions available that can help improve GenAI solutions.
It will be the year when conversations gravitate to GenAI, ethics, and what it means to be human. In some cases, we’ll start to see the workforce shift and be reshaped, with the technology helping to usher in a 4-day work week for some full-time employees. Talk around customer experiences will be dominated by AI’s impact, and we’ll see less focus on business intelligence. We can also expect to see a resurgence around IoT discussions due to AI kicking this into a higher gear with near-sentient robots doing things better and faster. In businesses, cybersecurity will be the “best worst” job next year.
More and better uses of LLMs beyond the workplace
Personal small language models will emerge that will help us with chores such as automating forms for schools and doctors and other time-consuming activities that AI can do faster and more easily. Sadly, GenAI will still be lagging in the “tell me a great joke” and other departments that require a real, functioning brain, so human creativity will remain at a premium. And one other thought … luddites will become their own market segment.