Belying expectations: Five tech letdowns of 2024
Subscribe to enjoy similar stories. Generative AI (GenAI) has shown immense potential since OpenAI’s ChatGPT gained over 100 million users within two months of its launch in December 2022. Unlike traditional machine learning (ML), which predicts data patterns, GenAI’s foundational models and large language models (LLMs) learn the structure of various data types—text, images, proteins, DNA, etc.—to create new content through prompts in natural languages like English or Hindi.
Companies are fine-tuning tools like ChatGPT, Bing Chat, Gemini, and DALL-E 2 to cut costs in customer service, content creation, and more. However, most businesses remain cautious, testing these tools rather than deploying them at scale. Challenges include hallucinations (generating false information and presenting it confidently as accurate), biases, intellectual property violations, high energy consumption, and uncertain returns on investment.
Goldman Sachs’ April report, GenAI: Too Much Spend, Too Little Benefit?, questioned the $1 trillion investment in AI infrastructure without clear benefits. Similarly, Gartner’s July report predicts that 30% of GenAI projects will be discontinued by 2025 due to poor data quality and escalating costs, which range from $5 million to $20 million. In India, the AI market is expected to grow by 25-35% annually over the next three-four years, according to Nasscom and EY’s 2024 AI Adoption Index.
While 75% of Indian organizations have AI strategies at the proof-of-concept (PoC) stage, only 40% are ready to move to production. GenAI adoption is slow, particularly in legacy sectors such as energy, utilities, and manufacturing, according to the report. While banking and financial services (BFSI), retail, and CPG
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