Enterprise Connect held an AI-focused event earlier this week in Santa Clara, and I was able to attend this inaugural event yesterday.
It provided the perfect venue to meet the ecosystem and get a pulse of AI adoption in the CX space:
Rapidly maturing landscape: I was so pleased to see how quickly the market is acknowledging the criticality of robust data platforms and data quality.
Results vs. cost reduction: Enterprises are seeing tangible results from AI projects, yet struggle to translate these into cost reductions. I maintain that this ability to "do more with the same" is underappreciated: the industry consistently underestimates the growing volume and complexity of customer service interactions.
The strategic roadmap imperative mounts: Despite results, boards and finance teams are demanding a path toward tangible ROI on AI investments. This pressure requires a strategic roadmap that charts the course for realizing the full potential of AI. Yet organizations continue to struggle with creating such roadmaps and effectively prioritizing use cases.
Cost assessment challenges: Determining the cost of AI is proving more complex than anticipated. The shift to consumption-based pricing models adds to the challenge.
Feature overlap dilemma: AI capabilities like summarization are now available across multiple product categories, prompting organizations to re-evaluate their technology stacks. This convergence of features is poised to reshape traditional category boundaries.
In-House development appetite: I left under the impression that a growing number of large enterprises are looking to build AI solutions internally. This trend is driven by a desire to get their arms around the technology and maintain control over technology choices in a rapidly evolving ecosystem.
Self-service is back at the top of the agenda. With the advent of GenAI and the risk of hallucination, human-in-the-loop use cases have been prioritized. The pressure for cost reduction has propelled self-service back to the forefront of the CX agenda.