5 habits for successful AI deployments

By Whit Andrews

Nearly half of CIOs say they now employ artificial intelligence (AI) or intend to within the next 12 months. However, many organizations still struggle to deliver AI beyond proofs of concept (POCs) and into production. According to Gartner research, over the past two years, only 53 per cent of POCs have actually made it beyond the lab into production, taking an average of 9 months.

Boards of directors, CEOs and customers want to use AI to power real improvements in customer and employee experience. But how to make AI a core IT competency still eludes most organizations.

Promoting positive habits to get the best value from the technology is an important way to make it more commonplace. The idea that your habits are strategic and intentional is key to understanding how to address AI in this modern capacity. Here are the 5 habits of enterprises that are the most successful in deploying AI, that all organizations can learn from to make their own AI projects successful. 

1. Use mixed-role AI teams for every AI project 

Organizations that have the highest effectiveness in making AI an integral part of business strategy use mixed-role AI teams for all AI initiatives. These organizations strongly believe that aligning AI to business initiatives is a way to deliver value. Both the diversity of the team and how that variety is applied across all initiatives is key. 

2. Invest in variety for the mixed-role teams (train members if you have to) 

Organizations where AI has “significant value” have 14 per cent more roles on AI teams. It’s most common to have roles like AI researchers and data scientists because AI always originates with data. Plus, it is key to have the technical acumen those roles bring on an AI team. 

In addition, roles like project managers, strategists, application designers and others are vital to the diversity of thought and background this type of work requires. Different backgrounds and perspectives on AI will improve AI ethics, an understanding of the value of AI to customers, how it should be used and where it can have the biggest impact. This will enable the team to deliver significant business value. 

3. Include top executives in strategy and funding

Organizations that assign AI budget to a corporate function at the C-level are more likely to reach a higher AI maturity level. Associating the budget with a sponsor at a high corporate level means the executive offers a sense of what the organization needs, so the AI team can address that and be the voice that explains the value AI has for the organization. They are able to communicate, at a C-suite level, how data aligns to business strategy and corporate goals. 

4. Do AI with a purpose and measure it 

Organizations that measure financial or risk impact for AI projects are more likely to be successful than those that don’t. Embracing metrics enables organizations to showcase how AI can be used across the enterprise by highlighting its benefits and risks in certain areas. For example, the ability to analyze videos or images might start in the security realm, but with some maturity could be used to analyze organizations’ brand presence or understand how customers react to products. 

This is not to say that every project must guarantee a positive ROI, but regardless of outcome, it must be measured to see what is possible. 

5. Limit the number of POCs

It might sound counterintuitive but do as few proofs of concept (POCs) as possible. In past years, one of the key messages organizations heard surrounding AI was to try everything and see what works, then focus on maturing what worked. However, organizations now increasingly understand what AI can do for them and when the technology should be avoided. 

Organizations that are now exploring AI in their operations do about 20 per cent fewer POCs than organizations that only plan to employ it. A deliberate approach to POC selection and deployment will deliver substantial benefits.

Gartner analysts will provide additional analysis on artificial intelligence and other emerging infrastructure and operations technologies at the Gartner IT Infrastructure, Operations & Cloud Strategies Conference taking place virtually December 7-10 in the Americas and EMEA.

Whit Andrews is a Distinguished Research Vice President at Gartner, where he addresses organizational impacts, use cases and business opportunities for AI.

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Jim Love, Chief Content Officer, IT World Canada
Gartner, Inc. (NYSE: IT) delivers actionable, objective insight to executives and their teams. Our expert guidance and tools enable faster, smarter decisions and stronger performance on an organization’s mission critical priorities. To learn more, visit gartner.com.

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