In 2024, organizations in every industry jumped headfirst into generative AI proofs of concept (PoCs). They were eager to harness the power of AI to generate content, automate tasks, and reinvent customer experiences. It was like the early days of the dot-com boom: limitless possibilities and undeniable potential.
Fast forward to today, though, the results are mixed. Some who invested in generative AI – the subset of AI that enjoyed so much hype in recent years – are thriving. They’re outpacing their competition, creating personalized customer experiences and launching innovative products faster than ever. Others are falling behind, and we’re witnessing a wave of PoCs being quietly abandoned.
This is where the divide is emerging – on one side are the winners of the AI race, and on the other are the losers. Organizations in the “win” column preparing for full-contact AI are taking the right steps to ensure success by prioritizing these trends:
- Focusing on data readiness. If they hope to see results from AI, organizations must invest in a sound, flexible data management infrastructure. Regardless of the technology innovations we’ve seen over the years, the conversation always leads back to data. Data challenges will persist for the foreseeable future, and the timeless rule remains: AI systems are only as good as the data they’re fed.
- Understanding that LLMs aren’t a silver bullet. LLMs can’t solve business problems on their own. LLMs are nothing more than statistical models of the distribution of word forms in text, set up to create plausible-sounding word sequences. GenAI can augment an organization’s existing processes to make them faster. But to get there, it’s critical to integrate LLMs into existing processes, data sources and business rules.
- Remaining flexible. AI is evolving at a breathtaking pace. All the more reason to avoid LLM vendor lock-in and unnecessary technical debt. Organizations that want to win with AI remain flexible and build AI frameworks to plug and play any model rather than building a framework to fit a specific model.
The future won’t be kind to organizations that fail to act on AI. Think back to the digital transformation wave of the early 2000s. Companies that embraced the internet, digitized their processes and invested in e-commerce became the Amazons, Googles and Apples of today.
Meanwhile, those who waited or followed the wrong adoption path either adapted too late, or disappeared. Those organizations are now irrelevant, if not out of business. Their failure to act meant competitors who did act, streamlined operations for efficiency. They created products and services unimaginable a few years ago. They attracted new customers. Those shaping the industry now were the first movers then.
AI isn’t a trend; it’s the next big leap in business.
