3 ways businesses can prepare as generative AI transforms enterprises

Investment in artificial intelligence (IA) has been booming for years and not slowing down. Some researchers expect the overall investment in AI push 500 billion dollars by the end of the decade. This is reasonable from an investor’s point of view. Venture capital firm Sequoia Capital, for example, has declared This Generative AI alone has the potential to generate trillions of dollars of economic value.

Generative AI – which includes trendy projects like OpenAI ChatGPT – is based on artificial intelligence technology that has recently matured and become publicly available. But we are reaching an inflection point as its potential begins to blossom and the money begins to flow.

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In fact, while generative AI currently accounts for only around 1% of AI-based data produced, it is expected to reach 10% by 2025, according to Gartner. This estimate may turn out to be conservative. Nina Schick, an AI thought leader, recently shared her view with Yahoo Finance that 90% of online content could be generated by AI by 2025.

This data can be used for countless business purposes and is about to completely change the way we think about work.

In other words, we are on the verge of a revolution.

How AI Evolves

So what is different about current AI developments?

With tools like ChatGPT, AI is now generating a new kind of conversation-like content that can entirely redefine the way we use and interact with data. This clearly has sweeping implications for creative professionals in fields such as education, marketing and business analysis, and it could portend a monumental change in the way their work is done.

However, what this means for those of us on the tech side of the house – and, more specifically, what this means for optimizing business processes and operations – is still unclear. Currently, there are no powerful, large-scale enterprise use cases for generative AI that will directly impact the top line and bottom line of today’s leading companies. But make no mistake, there will be and it will probably show up in a year.

Companies must therefore study this technology right away. Because what will separate the winners from the losers is knowing how to use it. And I believe that the key to success in using generative AI lies in understanding the primary and fundamental importance of data quality.

Why data is the skeleton key

Think of it like this: generative AI is, quite literally, data-driven. To be able to produce anything, you need a wealth of data ready to be analyzed. This is why investing in building and maintaining a clear body of data will be the most important element of a successful future in generative AI. It can massively accelerate the “learning” capabilities of generative AI-based solutions.

When data is as valid, accurate, complete, consistent, and uniform as possible across the enterprise, an intelligent generative AI tool can serve as the de facto digital assistant we’ve always dreamed of, serving teams of all departments and functions. Any question can finally find an answer.

Three actionable insights

So how can you prepare today for the yet undetermined future? Here are three actionable insights.

1. Invest in high-quality, “machine-learning-ready” data

With generative AI, you won’t need an abundance of data scientists at your fingertips to create relevant information and ideas. Instead, you’ll need a few experts who understand the underlying generative AI technologies, such as large language modelsand a full team responsible for ensuring that the data entered is the LAW data and in the correct format. AI can do all the analysis, leaving executives to focus on making the right decisions for the business.

In other words, it’s less about spending on AI and more about spending on exceptional data quality and management.

2. Prepare employees to adopt a new co-pilot

Generative AI also has the potential to change the paradigm for employees. With it, a new reality emerges in which employees work alongside a “co-pilot” who can answer any question and has a long-term memory of every topic ever discussed.

Encouraging employees to adopt AI as part of their daily work life will help workers optimize the technology for their specific roles.

3. Establish clear governance to limit risks

Technology is not always perfect and new innovations require a full assessment of potential outcomes and ramifications. It’s not just a matter of ethics; there can be real negative business consequences. What if your generative AI tool, for example, starts spitting out offensive content during your brand new marketing campaign? Are you ready for this possibility?

That’s why you need to establish clear safeguards to oversee and govern your AI technology. This includes a thorough assessment of the type of data you want to “expose” and provide access to generative AI-powered solutions. It’s not something that can run on autopilot, and we still don’t know how expensive or difficult it will be to scale. So we have to make sure we reflect All – and take a measured and strategic approach to protecting your future.

The prime time of generative AI is starting now and will dramatically change enterprise software. Details are yet to be determined, but the change is coming soon. Businesses should take advantage of this moment to prepare their data, policies and workforce for this emerging reality.

Yaad Oren is Managing Director of SAP Labs US and Head of the SAP Innovation Center Network.