When OpenAI launched ChatGPT in November 2022, I wondered if it would be as successful. Not that I was unconvinced about the potential of AI, but I was skeptical about its correct usage and potential biases.
Of course, it captivated everyone’s attention with its conversational ability to respond to any question, leveraging vast amounts of data it was trained on to identify specific patterns and make intelligent judgments. One of the most significant advantages that Generative AI tools have brought is the enhanced accessibility and increased productivity they offer.
However, the initial versions of Generative AI tools certainly had their flaws. CIOs were still determining their enterprise usage due to concerns around accuracy, security, and factuality to make it more suitable for enterprise use cases.
Fast forward to 2024, and an array of AI-powered tools has been launched, intensifying the competition among large language models (LLMs). Their capabilities have expanded from writing articles and content to creating PPTs, code, images, and more.
I have no reservations about acknowledging that my initial skepticism regarding Generative AI was too stringent. The launch of Generative AI tools like ChatGPT, Google Bard, and Meta Llama 2 has ignited a revolution, marking a significant stride in bringing AI to mainstream applications.
That being said, the future of AI relies heavily on gaining public trust. In 2024, AI is expected to play a crucial role in organizations and economies, as evident from our first ‘State of Enterprise Technology Survey.’ Over the next twelve months, businesses will use AI to improve customer engagement, offer personalized products, and enhance defenses against cyber threats.
However, choosing the proper AI framework, platform, and tools for organizational needs is becoming challenging. The global tech scene, widespread use of AI, and successful business applications depend on global AI governance. This governance is vital for protecting user data and ensuring responsible AI use.