AI Is Producing Improved Effectiveness and Efficiency in Both Customer-Facing and Back-Office CX Systems Across a Range of Industries and Use Cases

Dash Research’s report, “Artificial Intelligence for CX Applications”, focuses on the market drivers and barriers surrounding the adoption and use of AI in CX platforms, applications, and programs, the general use case categories for AI, and several representative case studies detailing the use of AI to improve CX. The report also details current AI regulations, which generally focus on the proper collection and use of personal information.

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According to Dash Research principal analyst Keith Kirkpatrick, the use of AI within CX can be classified under five broad categories: intelligent insights, predictions, preferences, recommendations, and automation. “Each step in the AI/CX continuum represents a progression of AI maturity and sophistication,” says Kirkpatrick. “As AI maturity increases, so does the required depth of integration of data sources within an organization, which can encompass customer and account data, product and service data, billing and fulfillment data, and service interaction data.”

Dash Research analysis indicates that there are four key market drivers spurring the adoption and use of AI within CX initiatives:

1. Increasing demand for customer-facing automation and assistants
2. Higher demand for backend automation and intelligent analysis
3. Growing appetite for data-led insights and customer journeys
4. More value seen with deeper customer engagement

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However, while AI is becoming part of the very fabric of CX platforms, like any technology or approach, there are technical and operational barriers to complete market adoption. Dash Research finds that the key remaining market development barriers include:

1. Limited scope or quality of data
2. Lack of alignment between CX challenges and AI solutions
3. Limited data governance policies and privacy concerns
4. Regulatory issues

Dash Research’s report, “Artificial Intelligence for CX Applications”, focuses on the market drivers and barriers surrounding the adoption and use of AI in CX platforms, applications, and programs, the general use case categories for AI, and several representative case studies detailing the use of AI to improve CX. The report also details current AI regulations, which generally focus on the proper collection and use of personal information.

Dash Research, the market intelligence arm of Dash Network, provides in-depth research and insights on the worldwide CX market including a comprehensive assessment of technology solutions, business issues, market drivers, and end-user dynamics across industry sectors. Dash Research’s global market coverage combines qualitative and quantitative research methodologies to provide a complete view of emerging business opportunities surrounding contact center technologies, customer data & analytics, customer data platforms, customer insights & feedback, customer relationship management, personalization & optimization, and employee experience.

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