Why and how to build trust in AI third-party platforms 

As recently as a few years ago, many businesses were still grappling with the decision of whether to incorporate data into their core functions and operations. While every company sat atop some store of raw data, many lacked the expertise, vision, or technology to make use of its data assets.

Today's organizations no longer have the luxury of choosing whether or not to use data in their operations. With digitalization accelerating dramatically over the past two years, any business that chooses to ignore its own first-party data resources puts itself at a severe disadvantage — one which their more technologically savvy competitors will be happy to exploit.

But once a business has committed to pursuing data-backed decision-making, it must choose how to build or acquire the tools and strategies needed for success. While early adopters of data analysis often designed their own bespoke solutions, modern businesses now have the option of choosing from a growing number of third-party business intelligence (BI) platforms to perform these same tasks. To better understand how large enterprises are handling this divide, I spoke with Dr. Vikash Raj, Head of Analytics and Process Engineering at IDFC Asset Management Company Limited (IDFC AMC). In his work at IDFC AMC, Raj has taken significant steps to advance the company's data practices; however, he recognizes that building trust throughout the organization—in both these new processes and in the third parties who are executing them—remains the most challenging hurdle for most companies in moving these initiatives forward.

Why consider a third-party platform?

For many organizations, the idea of turning over sensitive business data is difficult to accept. However, there are multiple factors that should lead most companies to consider trusting and deploying a third-party solution rather than building their own:

• Reinventing the wheel: Organizing, collecting, and analyzing data is no longer the Herculean task that it used to be. With the help of existing SaaS products and platforms, businesses can quickly ingest their raw data and begin deriving insights within minutes. However, choosing an entirely DIY approach is akin to reinventing the wheel, leading to higher costs, slower progress, and more painful headaches.
• Finding and retaining specialized talent: If a company chooses to build its own BI tools, it is then plunged into a frenzied market for specialized talent. Entry-level software developers are easy enough to find and recruit; experienced data experts with the skills to build a bespoke data analysis apparatus are another story entirely. Be prepared to pay for top talent, and to pay even more to keep them happy.
• Building buy-in: Transitioning to an insights-driven business culture takes time and will inevitably run into pushback. Choosing a third-party BI platform ensures that a company's digital transformation can hit the ground running, whereas a DIY project will likely provide naysayers with plenty of opportunities to criticize the new system.

Building trust in AI and third parties

So then, what should a business look for when they begin exploring the possibility of a third-party business intelligence platform? According to Raj, the process of building this trust should take place in three stages. The first stage is to build trust in the machine itself — in the concept of using artificial intelligence to process and analyze business data. As a company begins to use AI solutions, it must simultaneously work to change its culture from instincts-based to insights-based. This type of cultural change won't take place overnight, but it's essential for an organization to believe in the value of AI before it will ever be able to trust a third-party platform.

The second stage in building trust and buy-in is to conduct due diligence, testing, and processing to evaluate a potential third-party partner. An organization that is only beginning its digital transformation will need to understand the journey its data takes as it is processed by an external platform. Opacity or complexity should be avoided — any factor that discourages trust or understanding will have long-term impacts on buy-in and cultural change.

Finally, once an organization has identified a third-party partner, the third stage is to develop a long-term relationship of trust. Third parties must constantly prove their value through improved service and functionality. In the case of BI platforms, this could take the form of improved customization and accessibility, or the adoption of more proactive techniques that further simplify decision-making for the end-user. Over time, this type of partnership and trust in a BI partner can have a transformational impact, turning an organization into the type of data-driven business that separates itself from a pack of competitors.

In his work with IDFC AMC, Raj has found that the best solution is one that is trusted and can be easily used by any member of the organization. "We are trying to build a culture of self-service, data-driven decision making," said Raj. "A solution is only valuable to the company if it is adopted by the end-users."
Adopting business intelligence techniques — and ultimately entrusting their performance to a third party — is a step on the path to the higher utility. By turning over the most tedious, high-volume tasks to artificial intelligence, business leaders can focus instead on how to identify key business drivers, accelerate revenue, and better serve their customers. This transformation puts man and machine on equal footing, allowing each to maximize their impact on the organization's success.

Author

Kathy Leake, CEO of Crux Intelligence