A week with Amazon’s AI team and its partners revealed plenty of enduring optimism, but also a recognition that building effective generative applications takes work.
Nearly two years after ChatGPT’s debut, AI hype is giving way to reality. Companies are eager to build with generative AI, but they’re learning that doing so is hard. They’ve found that AI models are expensive, data conundrums abound, and “change management” isn’t so simple. To that end, only 21% of companies surveyed by Gartner earlier this year had GenAI in production, with the rest either “piloting” or “exploring” the technology, per data viewed by Big Technology.
What are the main challenges?
The primary challenges include the high cost of AI models, data management issues, and the complexities of change management. These factors make it difficult for companies to move beyond the exploration or pilot phases.
Why is change management so difficult?
Change management involves not just implementing new technology but also ensuring that employees are trained and processes are adapted to make the most of the new tools. This is often easier said than done.
What does the future hold?
While there is still a lot of optimism around AI, the road to effective generative applications is filled with hurdles. Companies will need to invest time and resources to overcome these challenges.
For more details, read the full article on The Wrap.
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