Challenges and Opportunities for Early Adopters

Over the past few months, ChatGPT has taken the world by storm and captured our imaginations.

Using computers to identify a cat from a random image was difficult, if not impossible. Last year, with the releases of DALLE-2, ChatGPT, and other AI generating tools, the public noticed the power of hint machines. Not only could we create pictures with cats on demand, but we could do it in any setting, context and art style, as well as an entire written story and narrative. What seemed impossible is now a reality, leaving many wondering “what’s next” and “how will this disruptive technology impact business and the world moving forward?”

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

Reduce mundane tasks with a Virtual Project Manager

Microsoft has released a new feature for its Teams messaging and conference calling product to use an advanced version of ChatGPT’s empowerment technology to automatically summarize, provide meeting notes, and assign action items to participants. These follow-up communications are critical to advancing white-collar work and typically take people up to 45 minutes.

Outbound sales and marketing

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

Unlocking organizational knowledge

I’m the person that colleagues ask, “have we ever done that?”, “do we have content around that?” etc. Much of that organizational knowledge is floating around on a shared drive or intranet, but it’s hard to find. Applying the techniques that allowed GPT-3 to accept textual data from human history can and will be applied to every piece of content a business creates…allowing anyone to ask the same questions to their AI and get an answer within seconds.

While organizational effectiveness is one area that businesses can use to do more, there are many opportunities to improve the customer experience.

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 deliver a fast, simple and engaging experience. Adobe has already begun using generative AI to enhance its Creative Cloud, enabling seamless image creation for creative professionals without leaving Adobe’s product platform. What seems new and exciting today will soon become commodity table stakes. In the future, creators will bring their ideas to life much faster, creating greater value for themselves (and Adobe).

Truly contactless trading

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

Imagine a world where instead of spending hours planning every aspect of a trip, you ask artificial intelligence: about another culture and city life, being realistic about what the kids can personally navigate, and also fitting within our budget, knowing we still have an anniversary trip in October. Can you provide multiple options?’

This AI not only cleans the web, but also uses everything it knows about you. This experience helps you plan and book a complete trip with one click, while giving you the confidence that your needs are taken care of.

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

The role of AI in privacy

The results of AI can be amazing, but knowing too much about yourself is scary and in the wrong hands can be life-threatening. Data privacy has come to the fore in the past few years, and this technology will require a redoubled. While consumers will expect a contactless experience, they will demand ownership of personal data. These trends favor organizations with a proven track record of assessing data privacy and require more on-device AI processing to help do so. Tim Berners-Lee (inventor of the web) refers to “data blocks” to support secure ways of accessing personal data so that you can be in control.

“Garbage in, garbage out” challenge.

Generative AI is only as good as the data that trains it, and if left unchecked, it can enable customer interactions that can be detrimental to brands. An early real-life example is when Microsoft launched chatbot Tay on Twitter in 2016 and had to shut it down immediately after it started making racist remarks. Most recently, the new GPT-4-powered Bing was forced to limit itself to shorter conversations after its wild examples confused users into thinking it was 2022, calling users liars and disparaging a popular, authoritative site as “information not a reliable source.” telling the user not to trust it. Google in particular is trying to take a slower approach to unleashing AI on the public to guard against these potential problems, knowing that if it happens, it could destroy their market share in search. A well-thought-out, slow, test-and-learn approach can help mitigate potential problems. However, in the winner-takes-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 shown us an exciting and somewhat terrifying future that is quickly becoming a reality. With that comes billions (if not trillions) of dollars in opportunities to navigate, along with many challenges and risks. However, one thing is certain. generative AI is here to stay.

Recent posts by Harry O’Halloran (see all)

Source link