Generative AI: Early Adopter Challenges and Opportunities

Within the last few months, ChatGPT has taken the world by storm and captured our imaginations.

Leveraging computers to identify a cat in a random image used to be difficult, if not impossible. Last year with the releases of DALLE-2, ChatGPT, and other generative AI tools, the public noticed the power of prompting machines. Not only could we generate images with cats on demand, we could do so in any setting, context, and artistic style, along with an entire written backstory and narrative. What seemed impossible is now a reality, causing many to wonder, “what comes next” and “how will this disruptive technology affect business and the world moving forward?”

From a business perspective, Microsoft, Google, Adobe, and others are aiming to monetize this technology to win future markets. Some tools have been released (or are in beta testing), helping businesses be more effective and efficient with operations and engaging with customers, essentially acting as a workforce multiplier.

Reducing mundane tasks with a “Virtual Project Manager”

Microsoft has released a new feature to their Teams messaging and conference calling product to leverage an advanced version of the technology powering ChatGPT to automatically summarize, provide meeting notes and assign action items to attendees. These follow-up communications are crucial to driving white-collar work forward and typically take humans up to 45 minutes to do.

Outbound Sales and Marketing

Generative AI also saves time when creating personalized sales messages or marketing collateral. Not only can you have emails, web content, real estate listings, etc. created with simple prompts, but if you don’t want to utilize Shutterstock to find a stock photo, you can have DALLE-2 generate one for you. This technology helps us do more with less.

Unlocking Organizational Knowledge

I am the person whose colleagues reach out to ask if “we’ve ever done this?”, “do we have content around that?” and so forth. Most of that organizational knowledge floats around a shared drive or intranet, but it’s difficult to find. Applying the methods that allowed GPT-3 to ingest textual data from the history of humanity can, and will, be applied to every piece of content that businesses generate…allowing anyone to ask those same questions to their AI and get a response within seconds.

While organizational efficiencies are one area businesses can use to do more with less, there are plenty of opportunities to enhance the customer experience as well.

Chatbot and Conversational AI for Customer Service

Soon, the next generation of chatbots will feel seamless to consumers, combining internal business knowledge with data to provide a quick, simple, and engaging experience. Adobe has already begun leveraging generative AI to enhance its Creative Cloud, allowing seamless image generation for creative professionals without leaving Adobe’s product platform. What seems new and exciting today is soon going to be table stakes in products. In the future, creators will turn their ideas into reality much quicker, generating more value for themselves (and Adobe).

Truly Frictionless Commerce

As this technology continues to evolve, it will enable the “truly frictionless commerce experience” brands have been talking about for decades.

Imagine a world where, instead of spending hours planning every aspect of travel, you ask an AI, “I’d like to take our family on a late summer vacation before school starts where we can enjoy nice weather, pool time, get a taste of another culture and city life, being realistic about what the kids can personally navigate, plus fit within our budget, knowing that we still have an anniversary trip in October. Can you provide a few options?”

This AI is not only scouring the web, but it’s leveraging everything it knows about you as well. This experience helps you plan and book the complete trip in one click while giving you the confidence that your needs are being considered.

What seems like magic to enable this experience leads us to one of the bigger challenges to solve…data privacy.

The role of AI in Privacy

The results of AI can be amazing, but knowing that much about you is scary and, in the wrong hands, can threaten livelihoods. Within the past few years, data privacy has come to the forefront, and this technology will necessitate doubling down. While consumers will expect a frictionless experience, they will demand personal data ownership. These trends give advantages to organizations that have a proven track record of valuing data privacy and require more on-device AI processing to assist in doing so. Tim Berners-Lee (the inventor of the web) refers to “data pods” to support secure ways of accessing personal data in a way that you can control.

The challenge of “garbage-in, garbage out”

Generative AI is only as good as the data that trains it and, if not checked, can allow for customer interactions that can be detrimental to brands. One of the early real-life examples is when Microsoft released the chatbot Tay in 2016 on Twitter and had to immediately turn it off, it began spewing racist statements. More recently, the new GPT-4 powered Bing had to be limited to shorter conversations after wild examples of it confusing users into thinking it’s 2022, calling users liars, and disparaging a known, reputable website as “not a reliable source of information,” telling the user not to trust it. Google is specifically trying to take a slower approach to unleash AI on the public to guard against these potential issues knowing that, if done haphazardly, this could decimate their market share in search. Taking a well-thought-out, slow, test-and-learn type approach can help mitigate potential issues. However, in the winner-take-all world we live in, being a slow mover can keep you out of the race altogether.

All-in-all, generative AI has opened Pandora’s box and given us a glimpse of the exciting and somewhat scary future that is quickly becoming a reality. With it comes billion (if not trillion) dollar opportunities alongside many challenges and risks to navigate. There’s one thing for certain, though – generative AI is here to stay.