According to a survey by process optimization company ABBYY, GenAI in the enterprise is mainly used for revenue-impacting analysis and employee productivity. Summarizing data is the most common use case, empowering employees’ ability to be more strategic. The primary drivers for initial adoption include increased efficiency, enhanced customer service and the ability to implement observed results. Responsibility for AI adoption for employee productivity is led by IT, said the ABBYY study. SoundHound AI, a provider of voice and conversational AI, has partnered with leading tech advisory firm, Bridgepointe Technologies, to bring its enterprise AI solutions to Bridgepointe’s vast customer base through its expansive team of expert advisors, consultants and engineers. SoundHound’s technology is designed to handle a broad variety of customer and employee interactions, including task completion, information retrieval and transaction processing. The Amelia 7 platform can handle complex multi-step user queries by orchestrating multiple AI agents with specific functions to answer questions, execute transactions and resolve problems via text or voice, without the need for human intervention. And unlike other agentic platforms, Amelia’s AI agents come with best-inclass automatic speech recognition (ASR), which means they can easily understand human speech, allowing customers to get things done just by speaking naturally, said the company. Amelia 7’s AI Agents use Agentic+ – a flexible combination of generative AI, multi-agent autonomous orchestration, traditional deterministic models and human-in-the-loop to complete tasks based on the best possible path to the right response. How GenAI is Being Used by Businesses Bridgepointe Partners with SoundHound to Expand Enterprise AI Adoption AI & AUTOMATION The Edge AI Market is rapidly emerging as a cornerstone of digital transformation across industries, driven by the need for real-time data processing, enhanced security, and decentralized decision-making, argued analysts at Polaris Market Research. The firm projects the global market will expand from $18.07 billion in 2024 to a whopping $108 billion in 2034, a CAGR of 19.7 percent during the forecast period. Defined as the integration of AI algorithms directly on hardware devices at the network edge, edge AI enables on-device computation without reliance on remote cloud servers. This capability reduces latency, lowers bandwidth costs and strengthens data privacy, explained Polaris. “Edge AI enables instantaneous insights by processing data directly where it’s generated — on smartphones, sensors, cameras and autonomous systems — eliminating delays associated with cloud roundtrips,” said the research firm. “This capability is especially critical in applications where milliseconds matter, such as autonomous driving, quality inspection systems and remote medical monitoring.” The global deployment of 5G networks is a major enabler for edge AI adoption, said Polaris. “The higher bandwidth and significantly lower latency provided by 5G infrastructure enhance deviceto-device communication and support large-scale edge deployments across smart cities, industrial IoT (IIoT), and next-generation telecommunication networks.” Edge AI Market Set to Explode In which areas have generative AI tools been deployed in your organization? Data analysis and insights generation (such as summarizing trends, predictive modeling, data cleaning) 62% Customer service operations (such as intelligent ticket routing, automated responses, call summarization) 52% Employee productivity (such as writing assistance, project management, etc.) 52% Automating document business processes (such as accounts payable, logistics) 50% Risk management and compliance (such as anomaly detection, policy summarization, audit preparation) 47% Sales and marketing optimization (such as lead scoring, personalized content creation, campaign optimization) 46% Customer-facing applications (such as chatbots, email campaigns, etc.) 44% Process intelligence (giving a holistic view of processes and where they can be improved) 43% Operations optimization (such as revenue and cost reductions) 43% Product development and innovation (such as idea generation, rapid prototyping, product design) 41% Source: ABBYY 10 CHANNELVISION | WINTER 2026
RkJQdWJsaXNoZXIy NTg4Njc=