Key Takeaways:
- AI adoption is accelerating, with 88% of C-suite executives recognizing its importance this year.
- Data management remains a key challenge for many companies as they try to optimize AI's potential, with a focus on organizing and securing data.
- AI automation is transforming business workflows, enabling quicker content creation across languages and distribution channels, but human strategy remains essential for success.
AI is dominating leadership conversations — and for good reason.
With 88% of C-suite executives predicting faster AI adoption this year and 51% of small and medium-sized businesses reporting over 10% revenue growth from Generative AI, the potential is undeniable.
Yet, many businesses remain in early adoption, grappling with data management challenges.
In our interview, Peter Leeb, VP of Commercial and Business Development at Veritone, shares expert strategies to overcome these hurdles and unlock AI's transformative power.
Who Is Peter Leeb?
Peter Leeb is the VP of Commercial and Business Development at Veritone. Prior to his current role, he was the co-founder of Kyro, a venture-backed and Google-supported, AI applications platform after spending eight years at Fox Studios. Over his twenty-year career, Peter drove many groundbreaking enterprise initiatives in e-commerce, digital distribution, digital marketing, franchise management, and technology. He has overseen over $1.2B+ in revenue, led new initiatives and expansion into international markets (China, Brazil, Australia,) and built several new technology platforms adopted by many of the largest global enterprises from Uber, and P&G, to JP Morgan.
A major challenge many companies have had to overcome is maintaining consumer trust and user-friendliness while expanding AI capabilities.
To this end, Veritone's aiWARE platform has been recognized as a leader in AI-driven solutions. Their AI platform understands, manages, and creates intelligence for audio, video, and text content.
“And specifically for each different industry sector vertical, there are different customized applications and solutions on top of the underlying platform that's tailored more towards certain industries,” says Peter.
“When we think of over the last 10 years, content and data have been completely unstructured. We've spent that much time across different industry sectors, being able to help customers ultimately understand everything going on in their video content, audio feeds, and texts, both at scale and being able to extract it on a frame-by-frame basis.”
Given that some organizations own 10,000 movies, television shows, trailers, short-form pieces of marketing content, or security camera footage, he points out that it is important to:
- Understand the content
- Identify it instantaneously
“Think next-generation searching capabilities, right? And then I need to be able to take action against any of those underlying data sources very quickly. That's what our entire platform helps them manage with.”
For example, the aiWARE platform is used by media and entertainment companies like Sony Pictures, which range from film and television studios to streamers and production companies: all rights holders of underlying content.
To better understand and use their content, they use the system to identify key frames.
“The same thing could be said in our public sector, where we're managing large sums of evidence on behalf of different companies, to be able to understand and add the intelligence to all of that information at the same time, to be able to instantly identify all of those pieces of content and take action against it,” Peter adds.
Expanding AI Capabilities While Building Consumer Trust
To put this into perspective, Veritone’s AI software powers Sony Pictures’ white-label applications, underlying content, and metadata.
“Hundreds of people across Sony and Sony’s partners can access their systems, anything they possibly want in real-time across the entire archive of film and television content,” he explains.
This data can be used for marketing, distribution, production, and post-production purposes across the entire media and entertainment supply chain.
In addition, this data can be accessed by third parties as well, on a case-by-case basis.
“Day in and day out hundreds of different users across cross-functional groups and organizations can go to the system and use it and pull whatever they want out of it.
In other cases, I look at it as a B2B2C or a B2B2B platform at the same time where they're accessing and inviting third-party partners.”
This means that social, video, and technology partners can also access the data or content, giving them flexibility and access points that involve everyone needed to create successful campaigns.
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However, AI ethics have a huge impact on sustainable business models and consumer trust. Peter believes it is a topic that has lived in the marketplace ever since more AI consumer applications have come onto the scene.
“And now everyone's starting to understand the fine print of terms and conditions, the fine print of how these models in an AI and machine learning world have been driven. Ultimately, we look at it as an ethical duty to secure the data on behalf of customers.”
He says the goal is to properly manage the underlying data across the board in an AI-driven world and to ethically allocate the rights amongst that content and data.
AI Ethics and Building Trust in Business Models
AI models today often scrape the internet and include copyrighted content under Fair Use laws.
Peter emphasizes that AI companies must manage and secure premium content responsibly for the future internet.
“We are in a data-driven world right now, and protecting the data ethically is our number one priority.”
He also stresses that companies must educate customers and act as data stewards, distributing content based on customer needs.
“In some cases, to be that brand steward and protect and distribute the data as our customers see fit.”
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Veritone helps customers use AI for efficiency, offering flexibility while considering trade-offs like cost, security, and performance.
"It's our responsibility... to give them optionality. What one model excels at, another might not and there are always trade-offs to consider — whether it’s cost, security, or performance."
Despite some resistance, AI is embedded at the highest levels of organizations.
"The reality is their data is not set up to achieve that end goal and solution."
His advice: Is your organization ready to optimize and deploy new tools?
Organizing Data for AI Success and Building Trust
Many companies struggle with scattered data across systems, making unified results nearly impossible.
Peter emphasizes that the first step is organizing and managing data effectively, as inconsistent approaches hinder progress.
“So step one in this whole equation right now is how are you managing and organizing your data?
I’ve seen four different answers inside of large companies, and the reality is until there’s one answer, you’re not going to be able to even test and deploy.”
Currently, about 95% of the market remains in the proof-of-concept phase, with only a small fraction achieving full-scale production. Despite this, tools are already delivering clear productivity and cost benefits in areas like customer service, marketing, and engineering.
“When you look at it holistically right now, we’re still in the very early stages of companies really trying to understand what they need to do to get to point two.”
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Ethical AI plays a critical role in this evolution. As a company focused on providing infrastructure, tools, and data sources to developers — not directly to end users — Veritone remains deeply committed to fostering trust in the B2B environment.
“I think we’re entering a next generation of rights management phase today that by no means is fully fleshed out across the industry. We’re starting to see collective standards and consortiums, which we’re involved with.”
“The worst thing we can have, both on a societal and business level, is a lack of trust, whether that’s between us and our customer or the customer and the end consumer.”
Peter also stresses the importance of helping customers protect their content, ensuring it doesn’t spiral out of control online.
Optimizing AI Models and Streamlining Content Workflows
Now, the goal is to ensure that models (including homegrown, third-party models, LLMs, and all types of different workflows) are managed and optimized based on what customers ultimately want.
“In the brand world, a lot of people talk about the creative output and the new tools and the new assets. There's not as much output right now,” Peter notes.
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“There's a copyright factor. There's a legal factor. I’m generating content out of my own IP, but using underlying models that are using it without licensed material. I'm not going to put that back out.
What is the output for a lot of the stuff? So I think collectively, we're all working on optimizing workflows, optimizing content supply chains right now.”
Making this all efficient in cost, human resource, and overall productivity workflows would equate to the holy grail for all enterprises.
AI Automation and Human Strategy Driving New Possibilities
This focus on streamlining workflows and boosting efficiency naturally raises the question: how do these innovations translate into measurable ROI for clients?
According to Peter, an overarching theme right now is using automation to transform a single asset into multiple versions across different languages and distribution points.
In the past, this would have taken between six and 12 months. Now, it’s a click of a button. However, he reminds us that despite the automation benefits, we need humans to still provide that final touch.
“We need humans to set the course of the strategies and plans and sentiment and distribution paths and in anything else right now.”
As Veritone continues to refine its AI solutions, the focus extends beyond streamlining workflows to exploring transformative AI technologies that open new possibilities for businesses across industries.
Peter highlights the company's excitement about both cognitive and generative AI:
“Being able to extract the concept of every single element in every frame of every piece of content, and being able to pull that out, whether it's face, sound, background, voice, you name it, our customers need every morsel of that type of information.
And then on the generative side, once we've identified that and once we have a mechanism and a toolkit to be able to leverage it, what more net new outputs, net new assets, net new content can they generate off of these base sources right now? And this cuts across everything.”
This combination of cognitive AI for content understanding and generative AI for creating new assets is changing the way Veritone’s clients manage and use their data.
By tapping into AI’s potential, businesses can overcome longstanding challenges and find new ways to drive value across different industries.
