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Recently, Tim Bachta, VP of Global Information Technology for Children International, and Andrew Welch, CTO of Cloud Services for HSO, presented at the NetHope Global Summit and discussed how AI can and already is benefiting non-profit organizations. During their session, Tim and Andrew discussed Children International (CI) as a use case, making the transition to the cloud and artificial intelligence (AI) to reduce costs and gain more insight into their donors and those they serve—and that it doesn’t take a big budget for any non-profit to scale their cloud ecosystem to start using AI right away.
The Children International story: A journey to digital transformation
For over 20 years, CI managed all its sponsor, donor, and child family information using an aging client-server architecture, complete with onsite servers and data centers.
According to Bachta: "We had a lot of technical debt interwoven with that, our website, many different single applications built around these, because that system had been around for so long. Did we want to continue to invest our time, money, resources, and effort into maintaining a data center? Or did we want to leave that to professionals? Personally, our job, our focus, our mission isn't managing a data center, and I didn't want to stay in that realm. So, we looked at Microsoft as a partner."
Over the past three years, CI has gone from a client-server architecture to a more cloud-based, cloud-focused methodology.
"One of the many benefits CI has been able to realize," said Bachta, "is leveraging cloud technology and AI to help many areas throughout our organization, not just IT, but also our program side, our marketing side, fundraising side, as well as of course technology side."
CI looked at all its systems utilizing the six Rs:
- Remain – Determine which elements of the current ecosystem will remain with little or no changes.
- Rehost – "Lift and shift", migrate existing on-premises servers to the cloud.
- Refactor – Optimize using tools like Power Automate, RPA, and mobile extensions.
- Rebuild – Create custom Software-as-a-Service (SaaS) solutions built from the ground up with cloud services.
- Replace – Entirely replace or absorb the workload into other truly SaaS-based solutions.
- Retire – Eliminate workloads, infrastructure, and associated costs of obsolete business activities.
Bachta continued, "We started by Rehosting our website and instantly saw savings in terms of our expenses and the manual effort needed to maintain it and keep those systems up and running. We were able to implement a lot of automation as we moved things to the cloud, which helped a lot."
For Refactor and Rebuild, CI had to address the many custom and ancillary applications it had accumulated that were being hosted on premises. "These were the applications we work with to communicate with our sponsors, or children, and our families in the field," said Bachta. "We completely rebuilt them in a cloud-first mentality."
To address the applications to Refactor and Retire, Bachta's team took a critical look at old processes it could replace by leveraging cloud technology. "COVID forced us to adopt cloud-hosted technologies," he said. "It moved us off of our file systems that were in the office to Teams. So, we were able to migrate a large number of files up to Microsoft Teams and Office in the cloud…2024 for us is the year of the big migration. We are actively migrating sponsors, donors, and children onto our new Dynamics management system."
By 2025, CI hopes to have no data centers or VMs and be 100% cloud-hosted and cloud-native.
Technological innovation makes even greater innovation possible
Over the last 30 years, technological innovation has been accelerating. Welch noted that the internet made cloud technology possible, making technological innovation much more affordable. The pace of innovation has accelerated to the point where AI is possible. Now, AI itself is accelerating that pace of change.
"We're moving," said Welch, "from what we call activity-based value to system-based value." He continued, "In the past, the value to an organization was implementing a new application to perform a specific task, like donor management, finance, or HR. What we see now is that the marketplace is gravitating towards what we call system-based value, where really the value to the organization is in assembling disparate parts of cloud technology in order to apply it for the broader whole across the organization."
Building an AI strategy moving forward
With AI at the forefront of technical innovation, all organizations, from businesses to educational institutions to government and non-profits, should include a strategy to incorporate AI into their digital transformation.
But how do you invest in AI technology so that you do not become one of those organizations that are getting left behind as the more innovative organizations pull away? And how do you know what technologies to invest in?
Welch offered two suggestions for implementing AI successfully:
First, position your technology investments to accommodate the innovations that will emerge in the future rather than trying to implement a full-scale AI solution today. According to Welch, "You need to think in terms of absorbing tomorrow the changes that you don't fully grasp today. The pace of innovation and technological change in this area is so fast that we don't have a firm idea of what will be coming in 12, 24 months, let alone five years. So, you have to invest wisely and set yourself up with the greatest probability to absorb tomorrow what you don't grasp today."
Second, focus on your data. Said Welch, "AI relies on data. It needs clean, consolidated data. But cleaning your data is an important step to take for reasons that have nothing to do with AI, such as reducing regulatory risk, reducing the risk of data breaches, improving your ability to run analytical workloads, or better reporting and business intelligence. So, data platform investments are very, very sound investments right now because they not only position you to be able to use AI technology that is just becoming available, but they also serve other benefits to your organization as well, and I think that that's a fundamental principle to apply here."
Welch shared five pillars of the framework used for CI to build and execute its future-ready AI strategy:
- Data Consolidation – Consolidate your data into storage services that can be aggregated and used by AI.
- Data Readiness – Clean and catalog the data to make it searchable and indexable. Establish rules for data security, governance, and compliance across the organization.
- Incremental AI – Slowly introduce speed, efficiency, scale, and accuracy to activities a human would have otherwise performed.
- Differential AI – These are the moonshot investments you make in AI, valuable scenarios because they allow you to jump out ahead of your competition.
- Scaling AI – Scaling and sustaining your investment in AI and the data platform it depends on.
Steps to introduce AI at your organization
Bachta explained how Children International rolled out its AI program and offered tips to other non-profit organizations interested in doing the same:
- Turn on AI you already own (or can easily acquire) – Implement Microsoft's extensive and growing range of Copilot products that are likely to be most impactful to you.
- Ask your people – Directly ask end-users and line of business owners to identify pain points in their work and their wish lists for AI assistance.
- Rationalize your workloads – Consider AI capabilities as part of any app rationalization or workload prioritization exercise you conduct.
- Mine your processes – Using tools like Process Advisor in Power Automate to identify pain points in business processes that AI could mitigate.
- Engage with your partners and peers – Keep your ear to the ground with peers and industry groups to understand how they're using AI. Local AI user groups are a great start.
Bachta explained, "At CI, we noticed that we had data in multiple places. We started aggregating the data and continue to bring in more data from different locations. AI allows you to wall off your data and leverage it for your own purposes. It does not have to go outside the organization. You can actually use your data as part of these AI large-language models. And it's in a safe environment. In fact, that data is not going outside your zone.
"And so, we've done things like leverage the AI chatbot with our global intranet, where you can now go on chatbot and ask it questions, and it'll quickly go through and search, and give you the answers, and then give you where it's cited from."
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