3 Ways Your Business Can Prepare When Generative AI Transforms Your Business

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Investments in artificial intelligence (AI) have been booming for years, and the momentum is undiminished. Some researchers expect total investment in AI to reach $500 billion in his decade. This makes sense from an investor’s perspective. For example, his venture capital firm Sequoia Capital says generative AI alone could create trillions of dollars in economic value.

Generative AI — including topical projects like OpenAI’s ChatGPT — is based on AI technologies that have recently matured and become available to the public. However, we are reaching an inflection point as that potential begins to blossom and money begins to flow in.

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In fact, generative AI currently accounts for only about 1% of AI-based data being generated, but is expected to reach 10% by 2025, according to Gartner. This estimate may prove to be conservative. AI thought leader Nina Schick recently shared her view to Yahoo Finance that by 2025, 90% of online content could be generated by her AI.


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

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

How AI is changing

So what makes AI development different today?

With tools like ChatGPT, AI is now generating new types of conversational content that can completely redefine how we use and interact with data. Clearly, this is having a fundamental impact on creative professionals in fields such as education, marketing, and business analytics, and could result in major changes in how they work.

But what that means for our technology side, or more precisely, for optimizing business processes and operations, remains to be elucidated. There is currently no large-scale, powerful enterprise use case for generative AI that directly impacts the bottom line and bottom line of today’s major businesses. But make no mistake, it could emerge within a year.

So companies must be researching this technology right nowBecause what separates winners from losers is knowing how to use it. I also believe that the key to successful use of generative AI lies in understanding the fundamental and fundamental importance of data quality.

Why the data is a skeleton key

Think about it like this: Generative AI is literally data-driven. To be able to output anything, we need rich data ready for analysis. Investing in building and maintaining a well-defined data corpus is therefore the most important factor for the success of the future of generative AI. It can significantly accelerate the “learning” capabilities of generative AI-based solutions.

When data is as valid, accurate, complete, consistent and unified as possible across the enterprise, intelligent generative AI tools can act as the de facto digital assistants we have always dreamed of, empowering all You can serve departmental and functional teams. Any question may be finally answered.

3 Actionable Insights

So how can we prepare today for a future that has yet to be determined? Here are three actionable insights.

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

Generative AI eliminates the need to have an army of data scientists on hand to build relevant intelligence and insights. Instead, a few experts who understand the underlying technologies of generative AI, such as large language models, and a complete team dedicated to making sure the data coming in is correct. you will need a team. right data and in the correct format. AI can do all the analysis so leaders can focus on making the right decisions for their business.

In other words, spend on good data quality and data management, not on AI.

2. Prepare your employees for the new co-pilot

Generative AI also has the potential to change the workforce paradigm. This creates the new reality that employees are working with a “co-pilot” who can answer any question and has a long-term memory of all topics ever discussed.

Encouraging employees to adopt AI as part of their daily work can help them optimize technology for their specific roles.

3. Establish clear governance to limit risk

Technology is not always perfect and any new innovation requires a thorough evaluation of its potential consequences and impacts. This is not just an ethical issue. It can have a serious negative impact on your business. For example, what if a generative AI tool starts spewing offensive content during a new marketing campaign? Are you prepared for that possibility?

As such, we need to establish clear guardrails for monitoring and governing AI technology. This includes deeply evaluating what types of data to “expose” and allow access to generative AI-based solutions. This is not something that can be done on autopilot, and it remains to be seen how expensive or difficult it will be to scale.So we have to make sure we are well thought out all – And we take a cautious and strategic approach to protect your future.

The heyday of generative AI has begun, dramatically changing enterprise software. Details are yet to be finalized, but changes are coming soon. Businesses should take advantage of this moment to prepare their data, policies, and employees for this new reality.

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

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