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Upbound 2024 Predictions: The Standardization of AI Tooling and Platforms


Industry executives and experts share their predictions for 2024.  Read them in this 16th annual series exclusive.

The Standardization of AI Tooling and Platforms

By Sumbry, VP of engineering, Upbound

With the rise of hot artificial intelligence (AI) tools, every company and person seemed to be experimenting with AI in 2023. There is no going back: AI will continue to play an evolving role. 

AI and platforms

I predict that 2024 will be more about standardization on AI tooling and platforms. It's still the Wild Wild West with AI, but with more maturity will come more standardization and out of the box solutions. 

There will be a great reckoning. We're going to see a lot of the "garbage" that exists today-like low-value UX/UI on top of other platforms (like on top of ChatGPT)-will basically go away. This will happen since it'll get much easier for any platform engineer to run these AI stacks themselves.

Here's what other members of the Upbound team contemplated regarding the potential impact of AI on businesses this year.

AI and candidate-driven job matching

Lem Diaz, head of people at Upbound, says:

"I predict that AI will become more prevalent in conversational job matching. Job seekers will begin to see more interactive tools to help them navigate the front end of their job-seeking journeys. This may include things like asking questions about the company's culture, strategy, competitive landscape, tech stack, funding, and other factors and getting a list of matches. These interactive models will enrich a job seeker's understanding of their potential fit and whether or not to pursue a position at a company. This will begin the shift from employer-driven job matching to candidate-driven job matching. It'll still be nascent in 2024, but I believe it will mark the beginning of this shift powered by AI."

AI makes marketing less tedious

Kelsey Havens, head of marketing at Upbound, notes:

"AI will become less of a buzzword in marketing and more of an integrated feature in existing marketing tools and technology. Tedious and repetitive tasks like ad sizing, sequence writing, tagging and task management will be offloaded to AI, giving marketers more mental space and time to be creative and strategic."

Cloud-native, multi-cloud infrastructure powers AI and ML

Tom Anthony, vice president of global sales and customer success at Upbound, adds: 

"In 2024, AI will make its way deeper into enterprises. I see this evolving in two ways. Cloud-native, multi-cloud infrastructure will be the fabric that enterprises standardize on to power their AI/ML initiatives. And, "AI-as-a-Service"- the ability for businesses to access AI tools and capabilities without having to invest in their own AI infrastructure or develop expertise-will become the way to drive faster innovation, productivity and cost savings within the enterprise."

It is clear the teams building the underlying infrastructure powering platforms, including AI and ML, have played an increasingly important role in companies. Here at Upbound, we're about making the lives of platform teams easier while helping them meet security, compliance, and policy standards. I'm convinced that creating platforms powered by control planes is a crucial step towards enhanced efficiency-a need that becomes more pressing as AI permeates all facets of the business. I talk more about this in a video on how to unleash the potential of your AI/ML platform with a Crossplane control plane.



Sumbry, VP of Engineering at Upbound

I am the Head of Engineering here at Upbound, the company behind the open-source project Crossplane. I have over two decades of experience working in the platform, infrastructure, and reliability engineering space at companies like AirBnB, Uber, and Twilio but have a non-traditional background. I started my career as a software engineer. I have taken on a variety of roles over the years from founder to network engineer, software engineer, platform engineer, system engineer, reliability engineer, engineering manager, engineering leader, and more. I started my early career in several startups as the Internet grew in popularity and quickly learned how to build and scale infrastructure, striving to strike the right balance between solving the right technical challenges while ensuring the business continued to grow. I eventually started several companies because I thought I had some excellent ideas but wanted to learn more about problem-solving from a product and customer perspective. Some great (and expensive) lessons learned are a big reason why I am heavily customer-focused today. I always have my customer hat on, whether one of business or engineering.

Published Thursday, January 25, 2024 7:31 AM by David Marshall
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