Sunday, February 5, 2023

Latest Posts

AI deployments: Is your organization a transformer, pathseeker, starter or underachiever?

AI-fueled organizations address strategy, operations, culture and change management and ecosystems, according to Deloitte’s latest State of AI in the Enterprise report.


Image: Deloitte

If your organization leverages data as an asset and scales human-centered artificial intelligence across all core business processes, consider yourself ahead of the game, according to Deloitte’s fourth State of AI in the enterprise report.

SEE: Hiring Kit: Video Game Programmer (TechRepublic Premium)

More about artificial intelligence

The study identifies four types of companies progressing toward this goal. One is Transformers, which comprises 28% of survey respondents and are considered to be “transforming but not fully transformed.” This group is using “leading practices associated with the strongest AI outcomes.” They average 5.9 out of 10 possible full-scale deployments on different types of AI applications, and 6.8% out of 17 possible outcomes achieved to a high degree, according to the Deloitte report.

The second are Pathseekers, which comprise 26% of respondents and are those who have adopted AI “capabilities and behaviors that are leading to success but on fewer initiatives.” This means they are making the right moves but have not scaled to the same degree as Transformers, the report said.

Twenty-three percent of respondents are deemed Starters, those who are “getting a late start in building AI capabilities.” They are also “the least likely to demonstrate leading practice behaviors,” the report said. They average 1.6 out of 10 possible full-scale deployments of different types of AI applications, and one out of 17 possible outcomes achieved to a high degree.

The fourth group are Underachievers, comprising 17% of respondents, according to the report. They have done a “significant amount of development and deployment activity,” but “they haven’t adopted enough leading practices to help them effectively achieve more meaningful outcomes.” They average 5.6 out of 10 possible full-scale deployments of different types of AI applications, and 1.4 out of 17 possible outcomes achieved to a high degree.

How to become AI-fueled

The foundation for AI success is typically built with a clear, well-communicated strategy, business-led work transformation, documented development standards, an adaptive workforce and a robust set of ecosystem partners, according to the report.

There are four cornerstones of AI-fueled organizations, Deloitte said: strategy, operations, culture and change management, and ecosystems.

Strategy. Transformers were three times more likely to have an enterprise-wide AI strategy. The tenets of that are to put strategy first, automate and innovate, share your vision and keep iterating.

Operations. Implementing new tech like AI often requires new ways of operating. Yet, about one-third of companies surveyed said that they’ve adopted leading operational practices. To do so requires ensuring that the business leads, reimagining workflows and roles, and putting MLOps processes in place.

SEE: Digital transformation: A CXO’s guide (free PDF) (TechRepublic)

“Technology cannot deliver transformative results unless organizations use it to reimagine how work gets done. Most leaders today understand this intellectually; however, survey results show a disconnect in putting it into action: Across a variety of operational activities—both on the business side and within IT or data science teams—only about one-third of those surveyed report that they have adopted leading operational practices for AI,” the Deloitte report said.

This includes adhering to a well-calibrated MLOps framework, documenting AI lifecycle publication strategies and updating workflows, roles and team structures across the business.

To ensure quality AI systems development, enterprise adoption and the most successful outcomes, organizations should rethink their operations across the business workflow and within their IT and data science team processes, the report said.

Culture and change management. Strong AI outcomes require trust, data fluency and agility. It is important to leverage change management to create the right culture because trust overcomes fear, data fluency drives creative insights and agility helps you fail fast, according to the report.

Ecosystems. When an ecosystem strategy is diverse and well-orchestrated, it offers flexibility, stability and perspective, the report said. Deloitte found that 83% of responding high-achieving organizations use two or more types of ecosystem partners.

Building dynamic ecosystems requires choosing partners with diverse perspectives and keeping things complicated, the report said. Otherwise, in the latter instance, “too few external partnerships can make it difficult to part ways with vendors if needed in the future.”

“Becoming an AI-fueled organization is to understand that the transformation process is never complete, but rather a journey of continuous learning and improvement,” said Nitin Mittal, AI co-leader, principal, Deloitte Consulting.

The firm said the report is based on a survey of 2,875 executives from 11 top economies who have purview into AI strategies and investments within their organizations. They were asked about a wide variety of behaviors—from their overarching AI strategy and leadership to their technology and data approaches and how they’re helping their workforce operationalize AI. The firm said it then analyzed the survey responses based on how many types of AI applications a company has deployed at full scale and the number of outcomes achieved to a high degree.

Also see

Source link

Latest Posts

Don't Miss

Stay in touch

To be updated with all the latest news, offers and special announcements.