What Are The Characteristics Of A Successful AI Team?

In this modern era, we have become increasingly reliant on Artificial intelligence to get the objectives accomplished. Since the goals are quite easily met by virtue of AI, organizations are not thinking twice before investing heavily in AI. However, a point that is worth a mention is that not all AI teams deliver the desired results. Some of the common reasons for this are inadequate data infrastructure, overhyped expectations, and lack of skilled resources. In addition to these, it is also observed that AI teams aren't able to deliver as expected because there are some capabilities that have to be worked upon such as optimized decision making, mining, etc.

On that note, have a look at what are the characteristics of a successful AI team.

Diversifying AI teams

With the resources being limited, the performance is being compromised because fewer minds mean fewer ideas, fewer identified problems, and fewer innovations. However, if the AI team is diverse, it is possible to uncover the problems and make better data connections. It is now time that the organizations take steps to add diverse roles and skills within the AI team. Importance should be given to not just technical roles like that of data scientists, data engineers, machine learning experts, etc., but also those with business domain, product management, user interface design, and software engineering skills. All this would ultimately result in a successful AI team – all set to achieve laurels for the organization.

Should be able to frame the problem well

It is possible to arrive at the right solution only when the AI team is in a position to sift through the complexities of the situation to frame the core of the problem accurately. Every individual within the team needs to take up the role of a translator. In doing so, the gap between technology and the business case is bridged. A successful AI team dives deep into data and tries everything possible to be able to understand the problem better. Well, there is more to it. Successful AI teams also exhibit empathy for customers and other users. This ultimately paves the way for solving problems holistically. Understanding the problem to depth makes the individuals creative, curious and innovative beyond imagination.

Scaling AI

Now, this might come as a surprise for many. However, what many tend to ignore is the fact that the best way to realize the full potential of AI is by scaling it across the enterprise. Many organizations struggle with their growth and fail to realize that scaling AI is the ultimate solution.

Not taking AI ethics for granted

Yes, scaling AI, framing the problem well and diversifying AI teams are all important but there is yet another aspect that deserves equal attention – the ethical aspect of AI. Adhering to the rules and regulations put forth by the regulators and policymakers is very important. A successful AI team understands what it takes to work within the framework of regulatory compliance quite well. Such a team would implement strong and auditable risk management practices throughout AI development, validation, and monitoring to build unbiased, interpretable, accountable, as well as reproducible AI systems that aim at delivering business outcomes that are fair and transparent. Ultimately, this is the prime goal of the organizations, right?