We Didn't Say It First, But Just Do It

Many say that 2019 was the year of innovation for nonprofits, with the sector taking steps to become more sustainable, developing leadership strategies with their boards, and embracing technology in their everyday operations. It has been obvious for some time that digital transformation has to be a near sight on the horizon for charitable organizations, and those that don’t have a digital plan of attack risk becoming obsolete.

But the year 2020 ushered in a new sense of urgency on digitization and the implementation of technologies like artificial intelligence. AI is no stranger to the for-profit sector, and nor are the challenges that come along with its adoption. This 2020 big data and AI executive survey shows 90.9% of firms cite people, process and culture challenges as the biggest barriers to becoming data-driven organizations.

This reinforces what we already know; change is hard, and it is particularly hard when it comes to ingrained ways of doing things. Implementing successful AI requires participation at all levels of an organization, and as people work more closely with AI technology, the nature of their work changes. Contrary to popular belief, there is no magic bullet when it comes to AI and no, you are not going to get an optimal solution that will work with your status quo operations.

AI will require a definite shift on multiple levels, and exploration outside of the thinking to which we are accustomed. Even something as standard as how we set goals will need to be rethought, are you setting goals that actually align with reality? AI trials measured by traditional metrics of success often don't make sense, because setting short term goals for a technology with such a long term value proposition has to be carefully considered.  

Then we are faced with preparing ourselves for these changes, and therein lies a huge problem for so many nonprofits; you can only do so much effective preparation for a largely unknown objective. We need to remind ourselves that artificial intelligence is still in its infancy in the nonprofit sector. While there is some planning and preparation organizations can do to make for smoother AI adoption before investing in the technology systems, nothing is going to prepare you for artificial intelligence like actually doing it.  

Everything we read about how to prepare for AI tells us that we need to sort out data governance first, and that’s not wrong. Data is the lifeblood of AI and how it is captured, recorded and stored needs to ensure its integrity and availability for use. Indeed, many organizations still lack the foundational practices to create value from AI at scale, and no clear strategy for sourcing the data that AI requires.

What is being neglected in the understanding of how to go about AI implementation, is that data governance and preparation IS actually the first step of AI. There seems to be a great deal of confusion between needing to do things in sequence, and segregating them completely. Therefore data governance and preparation need to be implemented alongside the technology systems that are going to rely on it. The idea that we should separate the two is flawed.

For example, a CRM transition is the perfect opportunity to get a lot of the data cleaning work done, and to make sure that your CRM is set up in a way that will accommodate AI. AI is like a muscle, it needs to be trained on your data and there is a huge advantage to having AI be part of the inception of your CRM. AI and data science are not add ons, they need to live and breath within your data infrastructure to be effective.  

Rather than trying to prepare for the unknown, the real first step to successful AI implementation should be to find a firm that is committed to working with you. And by working with you, this means working with a firm that understands the level of flexibility and compromise that is required for a prosperous partnership. The earlier you start, the more influence you will have on tailoring the systems to work for you before the software becomes more concretely established. Imagine the frustration after you’ve spent a couple of months or years executing on a plan to prepare your organization for AI, when you finally make the investment in the systems and software, you come to learn that it is not accommodating of the structure that your organization has spent so much time and money on putting in place.

There is no better time than the present to invest in AI, and it makes the most sense to do it with a firm that is going to help you through the whole process from the ground up. This includes everything from guidance on data governance to figuring out how to support your staff to work alongside AI applications. This will ensure compatibility between your organizational processes, and the AI technology systems.

There is such a long term value proposition with AI that people can struggle to see it, or lose motivation when faced with the long road ahead. It is easy to forget, as John Wooden once said, that “good things take time, as they should. We shouldn’t expect good things to happen overnight. Actually, getting something too easily or too soon can cheapen the outcome.”