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Enterprise AI leaders must consider the “AI HI Five” – five critical evaluation criteria for AI service partners

Home » Research & Insights » Enterprise AI leaders must consider the “AI HI Five” – five critical evaluation criteria for AI service partners

 

Your choice of AI implementation partners can make a world of difference in scale-up and adoption rates

 

Per a recent HFS study, a significant majority of enterprises who are adopting the emerging technologies from the Triple-A Trifecta of AI, analytics, and automation consider major consulting firms (72%) and new system integrator partners (70%) to be very important players (scoring 4 and 5, combined) to consider.

 

Exhibit 1: We know there is no AI without data. But there is also no AI without technology and services partners.

 

How important are the following type of third party software and service providers in helping implement your integrated automation strategy?

 

 

Source: HFS Research, “State of Integrated Automation” 2019

Sample: Global 2000 Enterprise Leaders = 317

 

 

When choosing the right partner for any of the Triple-A Trifecta technologies, evaluation criteria that covers certified headcounts and depth of technical competencies is necessary, but not sufficient. This rule holds especially true for AI, with its unique implementation challenges and long-term value realization periods. This POV lays out the HFS perspective on the five critical capabilities that will help your enterprise pick the right AI implementation partner to drive success and scale – initially and on an ongoing basis.

 

Consider these five critical capabilities while evaluating and choosing your AI implementation partners

 

AI implementation journeys are quite different from your typical large-scale software projects and technology implementation or migration programs:

 

  • AI use cases require extensive training on the domain and business processes. It’s not like software going live; enterprise leaders must embed the AI and automation technologies and use cases right into the processes that are targeted for transformation. It’s a completely new way of doing things.
  • The training and inferencing phases of AI programs often pose very different challenges for infrastructure requirements, runtime behavior, quality, feasibility, fitment, accuracy metrics, and relevance of output.

 

Therefore, maintenance, operational risks, and governance are much more important in the context of AI and automation implementation projects than the typical post-production tech support that most other enterprise software implementation projects require.

 

So let’s get beyond the obvious and give AI the unique treatment it requires. HFS recommends the following “AI HI Five” – HI of course stands for “help implementing”. Keeping these factors in mind, here are five capabilities you must consider while evaluating your AI implementation partners

 

 

Exhibit 2: The HFS AI HI Five – five essential evaluation criteria for your AI implementation partners

 

 

 

Source: HFS Research, 2020

 

HFS has cultivated this perspective from numerous enterprise client interactions. As a senior client leader in a global institute of higher education explained, “While the technical knowhow and quality of resources provided by the AI implementation partners were commendable, the consultants had a typical attitude problem. They always focused only on the low-hanging fruits, prioritizing the easiest-to-implement AI use cases. The consultants came across being extremely risk-averse and always attempting to brush under the carpet the challenges that were hard to solve, but were critical for the clients.”

 

Act now: choose your AI service partners right the first time

 

Enterprise AI leaders must take a long-term view while evaluating their AI services partners because the journey is long. Typical gestation periods of productionizing complex AI projects on critical business processes can range from one to three years. Keeping this in mind, we recommend putting the AI Hi Five into action as outlined in Exhibit 3.

 

Exhibit 3: Actioning the HFS AI HI Five – Action items for next Monday morning

 

 

Source: HFS Research, 2020

 

 

The Bottom Line: Enterprise AI leaders must evaluate the domain depths, and attitude demonstrated by their AI implementation partners, beyond just tech competencies.

 

Technical competencies and availability of resources are standard evaluation criteria for AI service partners.  Enterprise AI leaders must embrace the broader recommendations of the HFS AI HI Five which includes assessing implementation journey partners for their domain and outcomes orientation and their attitude toward taking on a client’s most critical challenges, not necessarily the easiest ones. This will help ensure the best partner fit and optimal outcomes.

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