Generative AI in Business: pragmatic use cases of Generative AI
As a kid I always enjoyed being in my own bubble, observing, listing to understand and - surely to great annoyance of my parents - ALWAYS asking "but why..."
The rapid pace of technological development is a testament to human ingenuity. Today, we find ourselves at the edge of figuring out how to apply this new thing... Generative AI. New technological kid on the block, whilst it big brother - AI - is often mis-understood.
Algorithms, Artificial Intelligence, Generative Pre-trained Transformers - holding so incredible much possibilities, speaking with people around me - I realize how complex it is to wrap our heads around anything that is different from what we know and easily spiraling into theoretic discussions around (Generative) AI.
As much as I LOOOOVEEEE a proper discussion (about anything, really) - I value to drive impact in what I do.
So, lets explore pragmatic, value driving use-cases of Generative AI. Outlining how you can leverage this technology.
What is Generative AI?
Generative AI is a subset of artificial intelligence that goes beyond the traditional concept of understanding and analyzing data. Instead, it creates or 'generates' new content, pulling from vast datasets to simulate human-like text, images, and even speech.
This technology hinges on complex algorithms known as machine learning models, especially those modeled on the human brain's neural networks. It's like having a digital Picasso or Shakespeare at your fingertips.
Sharpen your understanding of what Generative AI actually is here
Content Creation
1. Not-so-automated communication
As human / executive / manager / decision maker in a company - you'll find yourself jumping from conversation to conversation, juggling an abundance of projects simultaneously.
Thrown into the the lengthy email chain / teams chat / which-ever digital channel you must face to reply, considering the complexity of the conversation (not forgetting of everyone has their own version of what they really need to achieve) and a layer of other complexities. You know how to drive the conversation... but that initial start can be... put off to later.
Imagine you'd have your G'AI-ssistant* that pre-populated a draft. Including a voice over of the context of the advised draft. You stay in control, approving the message, perhaps 1 minute to tweak some words - before you send the message out.
*G'AI has been trained on your tone of voice, understands the complexity of the ongoing projects and is trained to be your senior advisor.
2. Marketing automation: content
You and the teams just spend x months ideating 20 (complex) automated journeys that will drive value to start with. Getting the data in which-ever systems and the deadline of the communicated launch of these fantastic value-driving journeys is steadily coming closer and closer.
Let's imagine we start with just 2 distribution channels in these automated journeys, email and SMS. Each journey has on average 6 touchpoints that need unique textual content.
6 x 20, leads to 120 unique pieces of content. - on par with your brand - and probably some form of personalization. Ambitious as you are, you also want some form of A/B or multi-variate testing in these automated journeys - thus minimum doubling the unique pieces of content to a whopping 240. Whoa...
How long does it take you / your team / the experts you are collaborating with to create a single piece of content, infused with a influencing principle ánd on par with your brand goals?
Not to forget, that content to be in line with the objective of what it is created for?
Seriously. How long would it take in the existing setup that you work with, to create 240 unique pieces of content for those 20 value driving automated journeys?
Now imagine that your G'AI-helper creates this content. The produced content is
Produced with a speed that is unmet. Frictionless. Like a well-oiled experienced machine.
The growth of content creation from 2001 to where we are today has exploded immensely.
A petabyte is a very big unit of data. It is equal to 1,000 terabytes, or 1,000,000 gigabytes. To put it in perspective, a terabyte is about the same as the amount of data in a 10-hour movie. So a petabyte is equal to 1,000 10-hour movies.
With this much content being produced already. How are you going to stand out?
Generative AI technology has the capability to create rich, engaging content. Be it drafting news articles, writing blog posts, or composing poetry.
With any technology that you use in a business context, be mindful how you ensure quality and accuracy. Put supervision, checks and balances in place.
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Conversational AI
1. This-could-have-been-an-email meeting...
How many meetings do you have per week, that evolve around finding a specific piece of information?
It is likely that that piece of information is documented. Somewhere. No one really knows where - and the people who made it, are either too busy or no longer work in the company.
Various studies of McKinsey, World Economic Form, Harvard Business Review throughout the years (2016 - now) show the cost for these type of meetings to be gigantic: an average of 1.8 hours per week per employee on meetings that revolve around finding a piece of knowledge that sits somewhere in the company. This equates to a total of $37 billion per year in wasted productivity.
What if your G'AI-helper, that is trained on the company context, can access and process all relevant documents, data and insights in seconds, has a log of what its been accessing and the G'AI helper continuous to learn... How much time you'd save with this technology?
Before spiraling into too complex of use-cases. Make it simple. Lets imagine you are a enterprise company with ±5.000 FTE. 1 global HR Centre of Excellence and local HR departments. How much time is spend every month on
If you can free up time from the way-too-full plate of the human expert with a technological helper, you'll enable the human to sweat the things that can make an actual impact.
2. Customer Support
Have you ever chatted with a customer service bot or asked a virtual assistant for help?
That's Conversational AI in action.
Do you tend to find yourself asking to have human to take over the bot when you are in the loop of misery, as the bot does not understand what you need?
Generative AI technology breathes life into these chatbots, enabling them to understand context, generate appropriate responses, and learn from past interactions. The result is enhanced customer service, seamless user experiences, and accessibility around the clock.
Maintaining data privacy and managing unexpected user inputs are challenges to mitigate before integrating this use case blindly.
Personalized Advertising
Lets imagine some more advanced stuff.
You are well under way with your business transformation. Having cut through the noise of mediocre-to-bad data quality. You've figured out how to harmonize and centralize your data. Transforming the data into actionable insights.
The automated conversations at scale from the marketing&sales experts have evolved from generic silo'ed approach to (micro)segments through a customer journey. Putting the customer at the heart of all the communication.
Generative AI brings a new level of personalization to advertising. Imagine a system that curates unique ads based on individual user preferences and behavior – that's the power of Generative AI. It can craft personalized messages that resonate with the audience, improving marketing effectiveness and fostering customer engagement. Yet, ethical considerations are put in place to ensure the personalization does not break the privacy relation.
Product and Service Innovation
The innovation landscape is ripe for disruption with Generative AI. Companies can leverage this technology to generate new product or service ideas, forecast market trends, or enhance existing offerings. Think of it as a brainstorming companion that offers a fresh perspective, unbound by conventional thinking. However, human oversight remains critical to assess feasibility and practical implementation.
Education and Training
Growing up in the schools I went to, I felt so out of place. A consequence of being grilled growing up having to do math, yet not understanding the methodologies being used result to this day, if I have to do math by head - my initial response is point blank freezing. As I'm a avid reader, context helps me to put things in perspective. The same with math and numbers. When I have the context for the numbers thrown at me - I'm a number magician (in a good way)
The education sector can harness Generative AI for personalized learning experiences and professional training programs. Tailored course materials, automated grading systems, and interactive learning platforms are just the tip of the iceberg.
With Generative AI, learning can become a more engaging and customized journey. Let's make sure we do not make the same mistake as we've done so many times already. Equal access how to use this these technologies to prevent a digital divide.
The Future of Generative AI
The potential use cases for Generative AI are limited only by our imagination. From creating artworks and composing music to aiding scientific research and simulating complex systems, the possibilities are endless.
As we move forward, it's crucial to navigate the challenges responsibly.
Should be at the forefront how we incorporate this new technology in our day-2-day
I'd love to hear your thoughts on Generative AI in the business context. Share your experiences, questions, or insights in the comments below. Less comfortable doing this public? Feel free to send me a message