Generative AI: The Insights You Need from Harvard Business Review
The world discovered Generative AI in the beginning of 2023. ChatGPT introduced over 100 million users to the possibilities of Generative AI. In less than 18 months society has shifted. With Wall Street and Madison Avenue literally banking on new markets, business, education and our globally connected society are witnessing transformation. Microsoft’s $10 billion investment in OpenAI is perhaps the strongest indicator of what GenAI will be expecting to produce. However, there certainly remains a big hill to climb.
New AI startups are creating GenAI business models around generating text, images, code and even animation and video via Sora at rather amazing speeds. GenAI is certainly altering how humans create content on a scale and speed not previously understood by society, government, business and education. So get ready for disruption.
This book will help understand the baseline of GenAI and the potential to change the world. Yet for the organization who decides to jump right in, make sure you understand Chapter 3:?A Framework for Picking the Right Generative AI Project. AI is not the web and GenAI is not html. Organizations must understand risk. Just ask Samsung and you will quickly understand why tech companies are banning GenAI within their internal networks.
A preview that is already playing
Chapters four to six are providing an overview or perhaps a preview of coming attractions: Gen AI is already disrupting creative work and is expanded by the augmentation of human creativity even with digital tools. And finally Gen AI is already changing sales as Microsoft and Salesforce have deployed GenAI sales-focused tools. In fact, the rapid adoption of Gen AI has created a title wave of rapid business ventures to capitalize on the hype cycle. Which brand will adopt and conquer and which will fade?
This introduces the fundamental problem with Gen AI. Tools like ChatGPT have a problem with bias and hallucinations. Their datasets are not accurate. In fact, verifications are bypassed in order to rush Gen AI tools into markets. Yet, this introduces another Gen AI service: tools to mitigate legal risks while ensuring compliance with laws and regulations.
The Prompt Engineering problem
Perhaps my favorite chapter of the book is Chapter 8: AI Prompt Engineering Isn’t the Future. The AI hype cycle has promoted a false mindset that Prompt Engineering is a career future. Yet even Anthropic’s senior Prompt Engineer admits AI will be eliminating this job in less than three years. So organizations should probably hold on making that $300,000 offer for a Prompt Engineer. This would be better understood if readers learn asking the perfect ChatGPT question is not as important as solving your organization’s workflow challenges.
Gen AI risk
The closing three chapters nine to eleven address risk and the concerns of jumping on the Gen AI hype cycle. I would nudge HBR to move these to the opening chapters: Eight Questions About Using AI Responsibly, Answered written by Tsedal Neeley. Please consider her book The Digital Mindset. Chapter 10 is focusing on risks of Gen AI. Finally Eric Siegel addresses both Wall Street and Madison Avenue in his chapter The AI Hype Cycle Is Distracting Companies.
So how is your organization avoiding the pitfalls of Gen AI data privacy, bias, and misinformation? Has your organization adopted guidelines to deploy Gen AI tools? And most importantly, what new value will Gen AI bring to your organization?
In conclusion, HBR’s Generative AI is a short valuable resource for everyone. Organizational leaders take note: start with the last three chapters to avoid the growing number of failed AI deployments since the launch of Gen AI.