Putting the “AI” in Team:
How a Winning Tech Stack
Changes the Game
by Max Vermeir, Senior Director of AI Strategy
As the artificial intelligence (AI) hype cycle continues to run its course, a collective consciousness of practicality and strategy in AI use has begun to play a larger role in how these solutions are utilized by enterprises globally.
Perceptions of AI-powered solutions have progressed from an initial “one-size-fits-all” mindset to a more goal-oriented and intentional approach, veering in the direction of solving specific business challenges and generating value in high-priority areas with a more acute understanding of AI’s strengths and weaknesses.
So, what’s the next step for maturity in businesses’ use of AI?
According to Forrester, it’s weaving an automation fabric that is capable of supporting complex end-to-end processes across the organization; an automation fabric that is comprised of key players, each excelling in their roles to tackle objectives that might have otherwise been impossible.
We see our customers currently navigating this approach, inspired to implement more AI-based solutions into their processes while ensuring that these solutions are both purpose-built for their business needs and positioned to augment their existing tech stack.
One customer, a leading global sportswear manufacturer, is putting the “AI” in team particularly well. They recently made game-changing strides toward expanding and strengthening their automation fabric, implementing AI-powered intelligent document processing (IDP) to integrate with their existing robotic process automation (RPA) solution and defining a strategy to incorporate a variety of AI-enabled technologies into a winning team.
Using IDP to make RPA more effective
After selling one of its large subsidiary brands, the sportswear company was faced with a massive document challenge: segregating and sorting 27 million documents associated with the two entities. Two and a half million of these documents lacked any standardized format, structure, or obvious indication of which document belonged to what company.
Wanting to take an AI-driven approach to solving this challenge, they decided to integrate ABBYY’s AI-powered OCR with their existing RPA system. The combined solution scanned the documents for specified trigger words, company codes, and other differentiating factors to sort them into the appropriate folder for each brand. As a result, the global company was able to successfully sell the subsidiary brand without any penalty or complications resulting from missing or errantly processed documents.
Without this strategic synergy of solutions, the manual processing and sorting of millions of documents would have consumed an unsustainable amount of time and resources, while increasing susceptibility to errors.
This use case isn’t just a proof point for the value of ABBYY OCR in processing large volumes of unstructured documents, but also a testament to the strength and efficacy of the global company’s automation fabric.
