Artificial intelligence may be the most-discussed boardroom topic to date, but just where on the maturity journey is the modern enterprise? It depends on a lot, actually. According to a 2024 global survey of 4,470 executives by Oxford Economics, only 18% of organizations are leveraging its full transformational power. The picture changes, however, when filtered by industry and region. The industries with the highest percentage of AI leaders currently are technology (45.7%), manufacturing and finance (tied at 45%) and healthcare (44.9%). Regionally, the United States, Canada and India are leading the AI charge, with Europe, the Middle East and several Asia-Pacific (APAC) countries in fast pursuit.
That disparity was not lost on APAC leaders speaking at the webinar, “Accelerate Your AI Strategy and Lower Risk with Quality Customer Data.” They stressed the importance of adopting AI early to secure a competitive advantage in the still-evolving region. “The gap between a technology innovation and a change or a revolution is so minimized and so narrow that we have to innovate and be at the cutting edge,” said Alex Koshy, Uniphore VP of Sales, APAC.
What’s holding enterprises back? It all comes down to data.
AI adoption, however, doesn’t happen overnight. It’s a process that starts with collecting data. Herein lies the problem for most organizations (and the reason 90% of AI pilots fail to move into production): most enterprise data simply isn’t ready for AI. Poor data quality, unstructured formatting and data governance challenges regularly impede enterprise AI initiatives. In fact, 41% of business leaders say they struggle to get the data they need, according to a 2024 AI Survey by Researchgate (sponsored by Uniphore). That’s the primary reason most enterprises are still in the early stages—exploration and experimentation—of AI maturity. They lack access to the high-quality data needed for total AI transformation.
One of the biggest holdups in the data bottleneck is recording data. Recording data is a goldmine of customer insights—or at least it would be if it was in a structured, AI-ready format. Fortunately, advanced enterprise recording software is making it possible for organizations to bypass traditional data barriers, transforming all recordings into usable AI-ready data. This rich, previously untapped data source is fueling countless new enterprise AI use cases and applications—including those using generative AI.
“Call recording is one of the oldest forms of how you get your Voice of the Customer, how you can work on analytics and generate intelligence,” said Gopinath Manian, SVP Hexaware Technologies “But, with generative AI—and all the transformative initiatives that are coming up because of AI—what’s happened is we are able to go up the ladder and move beyond just the recording. We can [now] index, pick up keywords, use various filters and [focus on] the simplest, high-priority item: what are we doing for our customers?”
Accelerating the maturity journey with AI-ready data
That capability to analyze and leverage recording data like any other AI data source is a critical first step in any enterprise AI journey. Those that do it right position themselves to accelerate their maturity journey and, consequently, outpace their peers. It’s something Koshy has seen firsthand working with Uniphore’s customers in the APAC region:
“We provide curated solutions which help [enterprises] transform from whatever stage of maturity of AI they might be in. We have companies and organizations which are high-end maturity on AI, and we have specific solutions that cater to such customers. We also have customers who are starting their journey, and we enable them to take that journey and be at the same pace with their competitors and others within the same field.”
What enterprises need to outpace the competition—and the market
Getting all data—including recording data—AI-ready should be priority no.1 for any enterprise on the path to AI transformation. From there, organizations can start planning which AI use cases and applications will have the biggest impact on operational efficiency, business performance and, of course, customer experience. Uniphore makes the entire process easy. Our multimodal AI and data platform, the X-Platform, provides a unified AI engine room, enabling enterprises to quickly and easily build, test and deploy AI projects using data from across the organization.
That includes valuable recording data, captured and rendered AI-ready by our enterprise communication recording solution, U-Capture. By introducing this rich data source into the larger enterprise data stream, organizations can uncover deeper customer and business insights and use them to develop highly accurate AI applications and even explore new use cases. And because Uniphore’s solutions integrate seamlessly with an enterprise’s existing infrastructure, organizations don’t have to start from scratch or spend excessively to start generating value from AI.
“Technology should never be a cost,” Praveer Inder Chadha, SVP Customer Management Services at Datamatics, told the audience. “Technology should be something that is self-funded from the efficiency that you get out of it.” At Uniphore, we wholeheartedly agree.
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