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The B2B technology market has been in a state of deep freeze for well over two years, since the Fed began increasing interest rates, raising borrowing costs, and making funding more difficult.
Mergers and acquisitions (M&A) activities, particularly in the customer experience (CX) and contact center as a service (CCaaS) spaces, have stalled. Meanwhile, the development of generative AI (gen AI) has initiated a proverbial gold rush for investors focusing on the rapidly rising technology.
Also: 4 ways to turn AI into your business advantage
Driven by the need to cut costs and manage operating margins amid an inflationary and uncertain economy, many business leaders are also pursuing AI adoption to replace their workforce across most departments with technology.
Although AI is not yet advanced enough to replace humans, the productivity gains it offers mean employees can do more in the same amount of time. Aberdeen's recent AI research indicates that, following cybersecurity, customer service is the second most common use case for enterprise AI. Technology providers recognize this trend and are quickly incorporating AI as a key pillar of their CX and CCaaS platforms.
In a move that underscores the rapidly evolving landscape of AI in CX, NiCE announced on July 28 its intent to acquire Cognigy, a fast-growing leader in conversational and agentic AI. Upon completion, the acquisition will integrate Cognigy's advanced automation capabilities with NiCE's flagship CXone Mpower customer service platform, a big step toward creating a unified CX AI platform.
The deal, valued at approximately $955m, is NiCE's first acquisition under new CEO Scott Russell and follows key strategic partnerships with AWS, ServiceNow, and Snowflake. With Michelle Cooper now leading NiCE's global marketing function, the company appears poised to accelerate its vision of an AI-first contact center, while keeping human experience at the core.
AI moves to the core of CX strategy
The contact center has long been viewed as ripe for transformation, marked by high costs, legacy technology, and siloed service delivery. Over the past five years, AI has played an increasingly central role in addressing these challenges, often supplementing existing tools.
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