Onboard your Copilot and AI journey
How to Develop an AI Strategy & Roadmap
12 Sep, 2024
Ahuti Kumar is an Engagement Manager at HSO International, where she leads Data & AI conversations with clients. She has a background in Information Science and worked as a data consultant, delivering projects in BI and data analytics. In addition, Ahuti has a clear passion for data and AI and how it can create business value. She enjoys engaging with customers, understanding their pain points, and finding solutions through the application of data platforms and AI. We asked Ahuti how she and her team at HSO onboard clients onto their AI journey.
Onboarding the AI journey with a holistic approach
Q: When clients want to kick-off their AI journey, where do you start?
"Clients almost always ask us: Where to begin? How to implement AI in their business? Who should be involved? And how is success measured? At HSO, we have developed a methodology for moving from these broad initial questions to crafting a tailored AI strategy and roadmap that addresses our client's unique challenges.
Our AI roadmap outlines specific use cases, both with immediate and long-term benefits, and the steps to achieve them. What distinguishes us is our holistic approach to AI, which encompasses not just point solutions but also data infrastructure, data migration, user adoption, security, and governance. This way we navigate them through the world of AI, including possibilities, prerequisites and risks"
Q: How does the HSO approach work in practice?
"Our methodology starts with an AI Briefing. For this event, we bring the IT team and the business, including C-suite management, together for a one-day workshop. It is important to have the business teams in the room, because it's elementary for success to connect business and technology.
The first half is set up to inspire. We bring everyone up to speed about the evolution of AI, its potential, and what Microsoft offers around AI technology. We also show various interesting use cases.
During the second part of the day, we host whiteboard sessions where we ask a series of questions about our client’s business challenges. For example: what events and operations impact their KPIs? What's driving revenue? What causes inefficiency within the business? When we have a good overview of their challenges and pain points, we start mapping them to relevant Copilot and AI technology and, from there, we build concrete use cases."
“HSO's extensive experience with ERP and CRM solutions positions us very well to deliver impactful AI solutions, as AI becomes increasingly integrated across business applications.”
From AI Briefing to AI Strategy and Roadmap
After the AI Briefing workshop, we go back and share our insights, including our view of the client’s level of data and maturity. Quite often, one of our first recommendations is to set up an internal AI Program, including a Center of Excellence that is staffed by their IT team, business leaders and an HSO team member to support and govern the various AI initiatives.
As part of the AI Program, we develop the strategy and roadmap, incorporating the use cases we’ve defined. We prioritize those with the quickest time-to-value and lowest costs.
A typical example of this type of use case is the Microsoft 365 Copilot, which can be implemented within weeks. Our roadmap also includes use cases leveraging Azure AI Studio and LLM models, which are relatively fast to build. As the organization’s data and AI maturity grows, we introduce more complex use cases, often involving machine learning and extensive analytics.
Copilot and AI are embedded in every business application
HSO's extensive experience with ERP and CRM solutions positions us very well to deliver impactful AI solutions. As AI becomes increasingly integrated across business applications, we help clients leverage the AI capabilities built into the Microsoft platform, for example during ERP transformations.
For instance, we are currently advising a service consulting firm undergoing a digital transformation. They aim to boost employee efficiency, recognizing their workforce as their most valuable asset. A key aspect of their transformation involves integrating AI and Microsoft Copilot from the start. This optimizes employee time utilization and minimizes repetitive tasks.
Another example is an AI Buddy chatbot, developed for a large multinational corporation implementing Dynamics 365 globally. The AI Buddy enables key users to skip having to go through hundreds of pages of documentation. They can just ask their question to the chatbot instead. Imagine the time saved! This tool accelerates adoption and saves the implementation team significant time.
Q: Concluding, where do you see the biggest risk of failing AI projects?
“What we find is that AI projects tend to be unsuccessful when they are developed in siloes, disconnected from the business. To me, the most important question when onboarding the AI journey should always be: what's driving value for our business?”
We guide you all the way
A note about AI and Data Maturity
Ahuti: “Depending on the type of AI application, a certain level of data maturity is required to successfully develop and implement AI."
"For example, one of our clients is eager to develop an AI solution to support and automate contract management with an LLM (large language model). However, in the assessment we found that most of the documents are on paper and need to be digitized first.
Building the right data foundation will probably require quite some time and effort. So having an operational data platform in place is critical to speed up your AI journey. Time to value is much faster if you have a good data foundation.”
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