What do Home Depot, JPMorganChase, Comcast, Lululemon, Kroger, Brinks, Tesco, Starbucks, Nike, Hubspot, Sweetgreen, Quantas, and Stitch Fix have in common? This group of companies cannot be more different in their products and services, and target customers. However, these companies share one thing in common – a recognition that AI (and generative AI) services and data collection and management are key a enabler to stay competitive and thrive in individual market segments. These companies are all using AI and analytics to improve and personalize the customer experience and journey when interfacing with current and potential new customers.
All customers are people, obviously, but it is surprising how many organizations fail to consider that ultimately it is people interacting with other people in a B2B context, or with systems, or processes, or workflows. The common denominator is people. Regardless of whether a company is in the business of B2B or B2C, the need to provide and regularly improve the people experience and data journey is increasingly being seen as a differentiator and positive brand attribute in the marketplace.
ChatGPT4 and other well-known large language models (LLM) include GPT-3 from OpenAI, PaLM or LaMDA from Google, Galactica or OPT from Meta, Megatron-Turing from Nvidia/Microsoft, and Jurassic-1 from AI21 Labs are gaining a great amount of hype since GPT-4 swept OpenAI and Microsoft's Bing into the lead, Google's Bard stumbled off the start line, and a number of others have joined the race by making their LLMs open for download, customization and training. For images, pixels are being lit up by Dall-E, Midjouney, and others. The introduction of LLM pre-trained generative AI has fired up the imagination of the public, and also content creators and entrepreneurs are creating add-on tools for many different use cases.
There are risk and caution indicators flashing. “If this technology goes wrong, it can go quite wrong,” said OpenAI CEO Sam Altman. In addition, 27,000+ individuals, including many eminent scientists and researchers, and one-time OpenAI board member Elon Musk, signed an open letter recommending a six month pause on further AI development while rules and guardrails and put in place to reduce the risk of harm to humanity. The US Senate's Judiciary Committee held hearings on AI recently to inform Congress of the risks and options to regulate AI and protect people against loss of privacy, fraud, identity theft, and misinformation. Several interesting ideas were discussed and generally there is consensus on a need for some regulation, and also, at a minimum, self-regulation by companies developing these LLMs while Congress develops a regulatory framework. What you might not see in the news coverage of the Senate hearing is the following:
- AI is still in early days of development and in 10 or 20 years, how people interface with machines will be drastically different than today.
- There will be no pause on AI development. Other countries, good, and bad actors are continuing to develop tools, services, and use cases for generative AI. Gary Marcus, Professor Emeritus New York University, prominent AI researcher and signatory of the open letter admitted he does not expect a pause will ever occur but signed the letter to raise awareness of the need for government oversight
- Accuracy will improve, bias will be reduced, and fail-safe mechanisms will be introduced into responsibly developed generative AI systems in the future.
What does this mean for companies of all sizes today? In short, if a company is not examining how AI can be introduced into its business, they risk a serious loss of competitiveness. AI enabled personalized customer experience and data journey, and efficient and accurate data management and robust governance in the back office will become the norm, and be seen as the Internet WWW (World Wide Web) was in the early days. That is a company was not seen as a serious competitor without a web presence and use of Internet enabled services. The potential for simplicity, personalization, and democratization of access to existing and new services will unleash a wave of creativity in new "AI-forward" service offerings and revenue streams. For several business-critical functions, introducing AI will require an upfront investment, but the payback could be significant when the aggregate positive benefits are itemized to include simplicity, better data and service management and governance, reduced operating costs, reduced or repurposed headcount, better jobs, and greater creativity and job satisfaction in company personnel.
Do you have a vision of an AI enabled organization? Or a strategy for introducing generative AI in your business processes, data management workflow, or customer experience? Or do you need one? Talk to us!
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