Generative AI: Help or Hurt the organization?

In the wake of advances in generative AI and large language models (LLMs), there is excitement about what this technology means for businesses. Chief executives, data leaders and AI experts are being scrutinised for their strategic next steps. From boosting productivity and reducing operational costs to finding new routes to revenue generation, generative AI could transform traditional business models. Running alongside this excitement is deep concern, inside the tech industry and beyond, that generative AI models are being developed too quickly blossoming into a new hype machine for the industry to follow with curiosity.

While other recent hype cycles have failed to deliver, is this the one that will deliver on its promises? The short answer is yes. It will not be immediately used in the ways that sci-fi thrillers would lead you to believe, but business leaders across every industry will deploy AI to augment today’s workforce by eliminating ordinary tasks. In fact, business leaders who fail to make GenAI deployment a strategic priority risk weakening their competitive position as peers streamline productivity and expand profitability, while at the same time improving employees’ experience by reducing the administrative burden. 

Technology vendors are recognizing the differentiated value GenAI capabilities can provide to augment their core offerings. Many of the largest cloud providers are making significant investments to capitalize on the opportunity, led by Microsoft ChatGPT, Google Cloud LaMDA & Amazon Web services updates for Bedrock and CodeWhisperer. 

But still the question that keep bothering the industry leaders remains as is that will GenAI be another emerging technology that gets stuck in Pilot Mode or will go beyond? The reasons behind such doubts are because hype cycles in technology are frequently traps that obscure the true disruptive power of innovation, presenting overblown scenarios that fail to come to fruition. Industry 4.0, for instance, provides a great example of a highly regarded trend that, at least within the originally anticipated timeline, failed to deliver on the promised outcomes. Originally dubbed Industry 4.0 as a mechanism for manufacturers to improve machine uptime, optimize output, and automate factories to improve operational efficiency and expand margins. However, the IIoT market has faced numerous development bottlenecks, many of which go beyond the required capital investment to either build net-new factories or retrofit existing factories with new technologies and machines to then digitize legacy processes.

Unlike Industry 4.0, GenAI’s near-term use cases do not appear to face implementation challenges. But this does not necessarily mean GenAI will smoothly sail into enterprise IT. Data privacy, for instance, is already emerging as a problem for enterprise customers, evidenced by recent developments at Samsung. Three software engineers at Samsung reportedly pasted meeting notes and source code into ChatGPT, releasing confidential data and information to OpenAI. Outside of enterprise concerns, regulators in the European Union, which have long been stringent around data protections and sovereignty, may restrict the use of third-party GPT models. Italy has already banned the use of ChatGPT within the country, citing data protections as a core reason, and others may follow. More crucially, the nascency of GenAI will require vendors to clearly articulate potential use cases to drive adoption.

However, despite GenAI’s nascency, business leaders are recognizing the benefits of this technology. Realizing the potential Generative AI offers, business leaders are increasingly keen to adopt it into their broader digital transformation roadmaps. They are seeing this as a powerful tool for innovation and problem solving. They believe that this technology can be used to automate complex processes, create personalized experiences for customers, and even generate new ideas and designs. The industries such as fashion, design, media, and entertainment, where the creation of new art, music, and assets by AI was previously unimaginable, GenAI is doing miracles.

While concluding this blog, one thing that I would like to say about GenAI is that it has opened the opportunities for growth, savings, and risk. This is up to the leadership how they accept it. They always have to keep in mind that Generative AI work as the ‘brain’ behind the digital transformation ecosystem whereas AI-powered automation serves as the requisite ‘muscle’ to act on the generated insights. Their implementation strategy will decide generative AI help or hurt their organization?

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Comments

  1. VimalSeptember 6, 2023 at 9:38 AM

    बहुत उत्तम. ये निश्चित रूप से डिसरुप्टिव है। अच्छा हो की इंडस्ट्री लेवल विवेचना और बेनिफिट एनालिसिस हो

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