Generative A.I is the hot topic right now - two key questions I get asked a lot. What's in it for my organization & how can I get started? Google's created some useful guidance on how to jumpstart generative AI across your organization.
No Question, Generative AI marks one of the most significant technological shifts in history. Recently read a very interesting guide to generative AI from Google which helped me think through its key applications, use cases and benefits.
What makes generative AI different from other forms of AI that have come before is its ease of use in helping solve everyday problems in people’s personal or professional lives.
Anyone who knows how to ask a question of a search engine can use everyday language to interact with a generative AI chatbot or virtual agent — getting it to answer questions, create, content, produce images, summarize documents, and much more.
Even better, a single generative AI platform can deliver solutions for multiple use cases, creating a network effect. As the number of users and applications increases, the model is exposed to more data and becomes increasingly accurate and useful — which in turn encourages more users.
Organizations that use generative AI to speed up, automate, scale, and improve business processes stand to reap big benefits. According to McKinsey & Company, generative Ai’s impact on productivity could add between $2.6 trillion and $4.4 trillion USD annually to the global economy. You’ll find more insights in McKinsey Digital’s insightful report on the Economic Potential of generative AI.
It's unlikely that any specific technology can take away the fundamentals of an organizations, value proposition and the core value chain in your industry. What can change, though, is how you use this technology to enable your teams to improve core offerings, and how you solve fundamental problems that get in the way of delivering them. With the right tools, you could even identify and deliver new points of difference, create new business models and find innovative ways to engage customers across your value chain.
We’ve all read and heard about some of the key productivity scenarios, enabled by generative AI– such as,
- Always-on coding collaborators
- Brainstorming assistants to draft and iterate content.
- Personalized self-education on just about any subject.
- Human-like interactions with customers wherever they need you, for whatever reason.
Generative AI is all these things and more. In time, it will affect almost every aspect of our Business and Personal lives.
At core, generative A.I has 4 capabilities – Creation, Summarization, Discovery & Automation. Based on these key capabilities, it tends to excel in applications- Chat, Search, Generating Content & Associative Reasoning.
In doing research on generative A.I, my focus is always on value creation and business impact. How can the advent of Predictive & now, Generative A.I deliver tangible, measurable business impact for organizations. The eBook provides interesting examples of how companies across different industries are experimenting with Generative A.I. I’ve curated some of the examples below - early days yet, however the results are encouraging.
Wendy’s is piloting an artificial intelligence (AI) solution with Google. It’s seeking to transform Wendy's drive-thru food ordering experience with Google Cloud's generative AI and large language models (LLMs) technology.
Scenario: With 75 to 80% of Wendy’s customers choosing the drive-thru as their preferred ordering channel, delivering a smooth ordering experience using AI automation can be difficult due to the complexities of menu options, special requests, and ambient noise. For example, because customers can fully customize their orders and food is prepared when ordered at Wendy’s, this presents billions of possible order combinations available on the Wendy’s menu, leaving room for
miscommunication or incorrect orders.
Solution: Wendy’s is beta-testing Google Cloud’s AI technology- automating its drive-through service using an artificial intelligence chatbot powered by natural-language software, trained to understand the myriad ways customers. The test will include new generative AI offerings, such as Vertex AI Search and Conversation and more, to have conversations with customers, the ability to understand made-to-order requests and generate responses to frequently asked questions.
Deutsche Bank is testing Google’s generative AI and LLMs at scale to provide new insights to financial analysts, driving operational efficiencies and execution velocity. There is an opportunity to significantly reduce the time it takes to perform banking operations and financial analysts’ tasks, empowering employees by increasing their productivity.
Time Magazine: For years, it’s been using AI-powered recommendations to build affinity and loyalty with readers. Now it wants to do more than deliver headline news — playing a bigger role as a beacon for accuracy. As media companies explore the possibilities of generative AI, the publisher sees an opportunity to strengthen its role as a trusted source and community builder. With generative AI, TIME hopes to turn a one-way conversation into a dialogue. Also came across this great article expanding on Time Magazine’s aspirations to leverage A.I.
Canva is an Australian global multi-national graphic design platform that is used to create social media graphics and presentations. Canvas is utilizing the latest AI technology to empower their customers and make the design process as frictionless as possible. From enabling users to translate their designs into over 100 languages with just a few clicks, to turning short videos into longer and more compelling clips with Google PaLM technology, they are unlocking the magic of AI with Google Cloud.
GA Telesis is a global aerospace platform with full-service aircraft maintenance and component services designed to keep clients flying forward. As a major supplier of essential equipment in the airline industry, where long-term relationships and trust are the bedrock of many business transactions, GA Telesis’ sales staff receive inquiries from global customers requesting quotes for all sorts of commercial aircraft and jet engine replacement parts.
Scenario: The typical inquiry is not standardized, requiring sales representatives to quickly decipher the relevant aircraft or jet engine model, applicable codes, quantity required, preferred condition and provenance, and often most importantly, where the part is needed and when. Additionally, in order for airlines to meet their on-time performance metrics, inquiries are often urgent, and logistics have to be factored into the equation. GA Telesis’ team is expected to accomplish what can resemble an impossible feat in minutes, not hours.
Solution: GA Telesis has selected Google Cloud’s Vertex AI Search and Conversation platform, which is designed to help businesses tune and deploy machine learning models, to help it quickly build innovative AI applications. Leveraging a new data extraction solution the GA Telesis technology team built internally, GA Telesis will be able to automatically synthesize purchase orders and quickly provide customers a quote, eliminating the need for sales teams to manually cross-reference emails with their inventory availability.
You can access the eBook for more details on jumpstarting generative AI.
