Sustainability and environmental, social, and governance (ESG) topics continue to take up space on enterprise agendas, leaving data, analytics, and artificial intelligence (AI) to "make a difference across" each of ESG's three dimensions, Gartner Senior Director Analyst Lydia Ferguson said.

The analyst firm reported 80% of enterprise boards expect to increase sustainability and ESG investments during the next two years. For modern organizations, that means working toward energy efficiency and decarbonization goals "is a mission critical priority," Ferguson stressed during a presentation at Gartner's Data and Analytics Summit.

On the environmental side, Ferguson highlighted AI's agricultural use cases like analyzing aerial or satellite images, weather patterns, vegetation health, and soil data. AI is also useful in simulations that, for example, predict wildfire risk and aid with prevention, spreading, and mitigation.

AI can also address workplace safety; diversity, equity, and inclusion (DE&I); and financial or pay equity, she explained. And in terms of governance, AI can align compliance and regulations, and it can monitor changes in local or federal regulation so enterprises can "stay compliant" or "quickly adjust their practices" if needed.

Although data, analytics, and AI "can be used for good," organizations should still assess the environmental footprint of large data sets and complex AI compute models, Ferguson noted. She recommends enterprises focus "on energy usage through more efficient hardware, more efficient cooling, residual heat usage, and renewable energy options."

In addition to carbon intensity concerns, Gartner VP Analyst Svetlana Sicular highlighted ethical and legal considerations that constitute responsible AI practices. "There is no black and white. It's about asking the right questions," Sicular told a group of reporters.

Legal considerations, while not always obvious, are the first kind that organizations need to address – like the right to be forgotten, Sicular noted. Regulations, she added, can be separated into existing AI regulations that enterprises have to follow and pending AI regulations that "are mostly in draft," she said. "They're not enforced, but they are coming and we know directionally where they will be going."

Sicular mentioned the ethical debate over whether ChatGPT should be considered an author along with concerns over data security with the OpenAI tool. "If you go directly to the link of ChatGPT, your data is there. They're training their model on your data," but "people don't realize it," she said.

Enterprises will likely encounter "many gray areas" when creating guidelines for the use of AI tools like OpenAI's ChatGPT. Sicular noted because social media raised alarms about potential ethical issues associated with AI earlier in the technology's cycle, "that gives me hope that we will do the right things," she said. "We as a technology industry already have seen the wave of social media where the reaction was fairly slow. And we know all the pitfalls and all the problems that are coming."