Getting Started on Your AI Journey

In ePlus’ last blog, Unlocking the Full Capability of AI, we explored the importance of planning and preparation before you embark on your artificial intelligence (AI) journey.

AI brings with it the potential for a major shift in the way we work. By 2025, nine out of ten organizations will view AI as a workforce partner, not simply a new tool.¹

Exploring the Possibilities

When it comes to AI use cases, the possibilities are endless. Best practices for deploying AI-powered technologies to deliver business value, however, depend on your organization and its goals. How do you get started? Begin by developing a strategy based on your desired outcomes and use cases, which will allow you to properly evaluate your AI preparedness and create a path to success.

Strategy, Outcomes, and Use Cases

There are many scenarios and outcomes to consider during the strategy phase. What capability or value does your organization want to unlock? What is the use case that will prove AI is transformational for your organization? For example, if you are in healthcare, can AI help you accelerate access to patient records and discharge patients more quickly? Can machine learning algorithms help doctors with disease diagnoses and treatment plans? If you work for a manufacturing company, can AI help you produce products faster with higher quality and less waste?

For AI to succeed, you first need to “know your why.” The strategy phase should define it. The output of this work should connect a business outcome (or outcomes) and a business initiative to an AI initiative and make the case for allocating budget and support to the project.

AI Preparedness

Are you set up for success to deliver on your initial AI use case? You’ll need to clearly define what is in-scope and out-of-scope to measure your AI preparedness for that use case. AI preparedness should focus on five key areas:

1. Data – Identify what data is in-scope, where that data lives, and if it is currently living across multiple silos or in a modern data platform.
   
2. Data Governance – AI models trained with bad data will provide bad outputs, and AI algorithms that index sensitive data could expose that information to people who should never have access to it.
   
3. Infrastructure – Can your infrastructure support the performance, scalability, and security demands of your initial AI use case’s workload, or do you need to evaluate alternative platforms?
   
4. Technical skills – Does your organization have the people and skillsets necessary to support AI-powered technologies?
   
5.  Organizational readiness – AI brings a significant culture change and full stakeholder alignment is critical to success.

Build vs. Consume

As mentioned above, many organizations will quickly realize that their existing infrastructure isn’t sufficient to meet the demands of their AI use cases and workloads. This leads to an inflection point of building AI-optimized infrastructure or consuming AI-powered services. The answer is different for every organization and every use case, so careful planning is required to ensure that your cost models match the expectations of the business.

Taking the Next Step

The first phase of the AI journey is not about moving fast immediately, it’s about getting you prepared to move fast. That means clearly defining your goals and strategy, selecting your initial use case, and then determining your preparedness. Given the pressure to leverage AI, the process can feel slow. But unfortunately, many organizations rush to start an AI initiative too soon, which often results in missed expectations.

Over the next several blogs, I will be covering each of the topics above in more depth to provide insights into successful, and unsuccessful, AI journeys that I have witnessed.

For organizations at the “AI Curious” stage who are exploring possibilities, assessing AI preparedness, and developing your AI strategy, ePlus offers several advisory services—from envisioning workshops to infrastructure and storage assessments and data governance—specifically focused on helping you unlock the full capability of AI. Check out ePlus AI Ignite for more information.

Sources

1. Gartner Says AI Ambition and AI-Ready Scenarios Must Be a Top Priority for CIOs for Next 12-24 Months. https://www.gartner.com/en/newsroom/press-releases/2023-11-06-gartner-says-ai-ambition-and-ai-ready-scenarios-must-be-a-top-priority-for-cios-for-next-12-24-months
2. Cisco AI Readiness Index. https://www.cisco.com/c/m/en_us/solutions/ai/readiness-index.html#blade_introduction
3. Ibid.