The six biggest AI questions facing companies today

Data is an invaluable resource for today’s enterprise. The large language models (LLM) upon which generative AI (GenAI) depends must be trained on data—typically lots of it. But quantity isn’t all that matters. Quality is also crucial. There is no AI exception to the “garbage in, garbage out” rule.

DataOps, DevOps, and cloud data platforms can all help here. Similar to how DevOps brings developers and operations together, DataOps maximizes the value of data by automating data management. Along with DataOps, cloud data platforms bring high-quality, optimized, consistently formatted data together in one place to break down the barriers between data creators and data consumers. Data can then move from being a raw material to becoming a currency to drive value. Data platforms also help address data security, privacy, and compliance concerns. All this paves the way for GenAI.

In the business world, entering a new era and a new paradigm with AI may require leadership transformation.

With leaders who are strategic, prepared, adaptable, empathetic, collaborative, and innovative, AI has the potential to help change organizations. But without that kind of leadership, AI can languish as another expensive point solution that further entrenches legacy practices and makes the organization more vulnerable to disruption.

We tend to talk about AI as an opportunity, but not every company sees it that way yet. Many business leaders are asking whether their entire ecosystem and market segment will be disrupted. Companies that resist disrupting themselves may be put out of business by competitors that do a better job embracing AI. Meanwhile, companies that invest in it, adapt to disruption, and redefine themselves are not merely surviving, they are thriving. 

The truth is that the AI evolution is just getting started. There’s still plenty of time for AI to work. Organizations that embrace it will unlock new business models and better processes that will keep them ahead of their competition.

In the future, the true value of AI will emerge by unlocking the possibility of brand-new business models, redefining organizations’ differentiation and positioning within their market segment.

Keep in mind that the future will not depend on today’s data, but instead on new data created by GenAI. Specific LLMs will infer and reason from a smaller data set. This will make LLMs possible on the edge, dramatically improving speed and availability. At that point, GenAI is no longer only an assistant or an agent, but an extended team member.

I don’t see AI as a threat; I see it as an opportunity. AI won’t replace the human spirit but will complement it, resulting in capabilities we have yet to imagine.