96
Finding Use Cases in Service for AI
View this email in your browser
The weekly newsletter of the Business of Tech, giving you new insights into the world of IT service delivery.
Looking for stories from the podcast stories? Check out the pod itself on Apple Podcasts, Spotify, or daily in your inbox. Stories are available to everyone for five days,and Patreon supporters forever.
Was this forwarded to you? Join the list!
Finding Use Cases in Service for AI
Now that consumers have gotten to know generative AI at a basic level, technologists and service providers are tasked with something a bit more complicated: distilling AI’s value within specific workflows and industries.
I wanted to talk to someone who’s tracking the key value adds of purpose-built AI applications, so I welcomed Yusuf Khan, the head of data science at Constellation, onto a bonus episode of The Business of Tech. He leads the development of innovative AI-driven solutions like Aurora, a social listening tool designed to enhance business strategies while filtering out misinformation.
From impactful AI use cases to advice for IT services organizations to predictions on the future of data collection, here’s an insider update on the state of AI implementation.
High-Level Trends, High-Impact Use Cases
I began our conversation by asking Khan about some of the most significant AI trends he’s observed in the last year.
He explained that although funding, research, and the productization of AI are continuing to increase, there’s also an increase in the ‘noise’ surrounding AI. Companies know AI has potential, but the challenge now is how to build it into their solutions in a way that actually adds beneficial value for the end customer.
“What systems like ChatGPT and these large language models have done is that they have democratized the use and access to using general-purpose AI systems,” he said. “There are always going to be these general purpose large language models. But the key value add will always sort of come down to looking at those models and trying to fit it into your product ecosystems to improve efficiency and productivity.”
So where are Khan and the Constellation team seeing some of the strongest impacts?
Because training and building models is an expensive task that most SMBs can’t necessarily take on, Khan’s work is focused on helping customize LLMs with Constellation’s data to help customers provide that downstream value. Right now, one of their specialties is the automotive space.
How to Be a Great AI Sommelier
Now, we IT folks, MSPs, and consulting organizations won’t be building our own LLMs, either. As I’ve illustrated before, I believe we’ll end up as AI sommeliers – if the large language model and the AI companies are the winemakers, we’ll be the ones taking those models as created and then pairing them with customers’ needs.
Khan was on board with this metaphor and even added one of his own: if LLMs and foundation models are refrigerators, then the real money to be made is with companies like Coca-Cola, who used the invention of the fridge to boost profits.
Whichever metaphor you prefer, Khan gave some advice on how to be the best sommelier or cold-goods provider:
“One of the key things to keep in mind is if an LLM is given 10 different or 10 same inputs, all of these LLMs, in a way, will converge… But if you have some data that is your own data, which you and only you have access to, now all of a sudden, the LLMs have another way to work with and address different types of pain points and questions that might happen, and that becomes very unique – that’s your value add,” he said.
Now and in the future, Khan believes the key will be excellent and creative strategies surrounding data. A lot of companies are rethinking how to monetize it already, but he also thinks this will be a wait-and-see situation. Approaches to masking, anonymization, clean rooms, proxies, and even government regulations are still shaking out.
‘Smart’ Data Collection
But what does it actually mean for a company to be really good at data? I ran this by Khan, and first and foremost, companies will need to develop a multi-dimensional view of their own data. Whether it’s hard data, an old database, or even videos like our podcast interview, he believes nearly all companies have some form of data worth exploring.
Then…
“Being smart with data sort of comes down to taking a step back, assessing what the data is, spending some time to come up with a strategy to try to understand, is my data proprietary? But more than proprietary, does it add value? Not just to my industry, but even outside of my industry,” he said.
Khan also explained that when Constellation personalizes a product, the data is not completely broad – it’s very contextualized to that specific industry, allowing them to get better responses from the LLMs based on that customer’s unique value props.
Contextual (and Misinformation-Free) Social Listening
This brought us to Khan’s main expertise: contextual social listening, powered by AI.
Historically, social listening has been the idea of looking at everything that’s happening online digitally and trying to derive metrics from it. The main challenge for the industry has been how broad these metrics shake out, plus the difficulty of parsing out what’s real vs. what’s based on misinformation and AI-generated content.
That’s why Aurora (Khan’s AI solution) does ‘contextual’ social listening:
“Aurora mines through a lot of this online information, like how some of these other social listening companies do. But most importantly, it connects that data back to some type of an identifier, which then contextualizes and zones it down even further,” he explained.
This adds two important things to the social listening results: more precise, industry-specific classification of qualitative to quantitative data, and an added layer of factual information checking.
Let’s zero in on the misinformation problem. How can Khan be sure that the information he’s looking at is valid?
The answer shouldn’t surprise you: AI. It’s not a bulletproof solution quite yet, but he believes it’s the best option we have right now.
“Because these AI systems are getting better and better, there is nothing that we would be able to do right now that would want to reach the accuracy of the future of these AI systems. But we do think that using generative AI to look at data and try to distinguish what is right from wrong doesn’t necessarily solve the entire puzzle, but it does get us a step further ahead in fighting false information,” he said.
Trends Worth Tracking
To wrap things up, I asked Khan what emerging AI trends and technologies service folks should be tracking right now.
In short, he thinks AI agents will grow in importance in the service industry. They’re becoming more precise, and with the right algorithms in place, will soon be able to improve our productivity greatly.
Are your clients ready for more focused, purpose-built AI solutions? How are you supporting their implementation? As always, my inbox is open for insights, stories, questions, or whatever else is on your mind.
More from MSP Radio
Missed Things?
How about our latest videos to catch you up?
The Daily Podcast available as videos
Sustainability, AI, and Growth in IT Services: Insights from Rackspace President Srini Koushik
AI Promise in Business Ops: Boosting Productivity, Labor Impact, & Ethical Concerns w/ Colin Britton
Exploring Open Source Solutions for Risk Reduction in IT Services with Doug Milburn
AI in Product Development: Enhancing Workflows & Minimum Iteration w/ Cody Schneider
Global Talent Management Strategies for International Recruiting in Today’s Market w Jonathan Romley
Building Diverse and Flexible Workforces with AI in Tech Hiring Strategies w/ Hugo Malan
Want the Daily News?
All the stories from the daily Business of Tech Podcast are available in the daily digest, and stories are available to everyone for the first five days, and Patreon supporters forever. Catch the audio of the show anytime on Apple Podcasts, Spotify, YouTube, or wherever you find podcasts. Links at businessof.tech
Copyright © 2024 MSP Radio, All rights reserved.
Want to change how you receive these emails?
You can update your preferences or unsubscribe from this list.