Market Topics
AI is both new and old. With roots dating back to the 1950s and even before, a new AI era bloomed in 2015 as cloud computing made AI compute workloads much more affordable. It was then, as a market research analyst with a deep background in mobile technology, that I started to delve into Slack’s pioneering “bots”—taco bot, cat video bot, etc.—and discovered these bot developers were leveraging elements of natural language AI to power their applications. Their work spawned early versions of enterprise-focused virtual assistants and consequently the biggest AI investments and commercialization: customer service automation. I was fascinated by the immense potential of AI, and quickly learned it wasn’t magic but rather an extremely complex technological breakthrough that requires equal parts technological experience, culture change and people/process transformation. I have been focused on telling the story and developing thought leadership about the pragmatic, business-driven market adoption of enterprise AI ever since.
While I’ve been a tech market research analyst for 16 years, my approach has been heavily influenced by a previous 10-year stint working for mobile technology vendor Syniverse. It was there, leading teams that were building new products, that I learned key principles that apply to operationalizing AI: 1) Start with asking what problem you are trying to solve; and 2) Take a classic business discipline approach—develop a detailed business case and leverage a gating process.
While the generative AI market is evolving at lightning speed, a pragmatic approach holds true even more so for generative AI than it does for legacy AI. Enterprise AI themes over the next few years will evolve around use cases, AI risk management, responsible use of AI, AI governance and observability and controls, cost management, AI model hallucination mitigation, build/buy/partner strategies, on-device (locally processed) AI, leveraging proprietary enterprise data and AI, the impact of AI regulations and standards, and more. AI hardware, services and software vendors must establish trust and confidence in the market to have any chance to succeed. These are the areas of AI I am excited about and plan to cover. My strength is helping AI vendors establish thought leadership and to tell their story in these areas to the audiences that are important to them—customers, prospects, investors—about how they are thinking about and addressing problems their customers are trying to solve.
The Move to Enterprise Strategy Group
Generative AI is a nascent market. As such, real-life data points that can anchor solid market analysis are very valuable to enterprises seeking to operationalize AI. I’m excited to join TechTarget’s Enterprise Strategy Group because primary survey research, which produces these precious—and unique—data points is foundational to the outputs the firm produces. Enterprise Strategy Group has a well-known reputation for its rigor and professional approach to developing and delivering top-level primary research and related outputs. Marrying that expertise with my passion, curiosity, and knowledge about AI is something I’m looking forward to.
