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AI 101

By Savannah Gibson
July 2, 2024

I need to confess something: navigating the realm of AI can feel like trying to understand a toddler’s abstract finger painting (on a good day). Whether you are a seasoned software asset management guru, or someone who thinks that Python is a large snake, there’s a certain naivety many of us share when understanding something as unprecedented as AI.

As SIE’s new Business Analyst Intern, and a fourth-year college student who has dabbled in generative AI for class projects (hello, ChatGPT!), I’ll admit to being a bit nervous when my SIE bosses asked me to write a blog post on “What is AI Risk Management?” Mind you, this request came on my first day as a summer intern. Eager to meet expectations, I accepted the task confidently. Of course, I know what AI is–I’ve seen the Terminator once or twice. But after spending a few days thinking about what to write, I finally admitted to myself how naïve I am related to the application and risks of AI. Especially when it comes to understanding everything AI offers to a professional services company that specializes in software asset management, such as SIE Consulting Group.

As I embarked on this new journey, I knew there would be a lot to discover. And as the world continues to expand into the realm of AI, there is quite a bit of learning to be done as well.

I figured I could manage this assignment in bite-sized pieces and started with a 101-level blog that I intend to build upon. So, what exactly is AI, and how does it fit into the software asset management landscape?

What is AI, anyway?

AI, or Artificial Intelligence, is the tech world’s attempt at creating a brainy assistant who never needs a coffee break. AI is the magic behind your voice-activated smartphone assistant and the reason you get suspiciously timed ads about that KitchenAid mixer you were just talking to your mom about.

A more generalized definition for AI: intelligence exhibited by machines, particularly computer systems. AI uses complex algorithms and methods to build machines that can recognize patterns, make decisions, and execute tasks based on the data or prompt provided. AI has different layers, which include machine learning and deep learning.

There are many different types of AI, including:

  • Generative AI
  • Data-Input AI
  • Image Recognition AI
  • Audio AI

With a basic understanding of “what is AI,” I wanted to answer for me and my employer: how does all this theoretical AI magic translate into the world of software asset management (SAM)?

AI in SAM

My employer this summer (and hopefully longer) specializes in professional services for software asset management. My coworkers are experts in helping large and complex organizations manage their software licensing and make sense and strategic decisions out of vast quantities of data. As I dive deeper into my role at SIE, I’ve been curious about how AI is revolutionizing the software asset management space. It turns out, AI isn’t just a chatbot or sci-fi concept, but a game changer for all industries, including SAM.

Why is AI a Big Deal for SAM?

  • Inventory data processing: The SAM world revolves around data: installations, usage, hardware type, consumption levels, just to name a few. One of the most impressive aspects of AI is its ability to process large amounts of data at once. For a software asset management professional services firm, like SIE, this means AI can process data efficiently and accurately, making it an invaluable tool for optimizing inventory. With promises to eliminate manual data entry, AI can process inventory and entitlement data in record time.
  • “Flat file” (or PDF) scans to intelligible data: AI can scan and ingest software contracts at high capacities and at record speed. This is crucial to managing compliance and understanding nuances of various software agreements. It can also eliminate the need for human input for data loading, which often results in errors or inefficiencies.
  • Predictive analytics: AI can predict trends and potential issues before they arise. This proactive approach is invaluable in avoiding costly mistakes and optimizing software usage.

SAM Technologies Embracing AI

As I learned more about how AI affects SIE's ability to provide software asset management services, I wanted to explore what types of companies or technologies were already operating in this space. Two I looked at include Terzo and Flexera.

Terzo.ai is an innovative, financial business intelligence platform, which uses AI to help unlock answers in contracts, invoices, and other financial documents. They are a vital asset to streamlining various SAM processes. You can check out more about Terzo and their cutting-edge solutions here.

Flexera, another key player in the SAM space, is using AI to transform the industry. Flexera’s AI capabilities help organizations manage their software assets more effectively by automating routine tasks, analyzing usage patterns, and more. For more details on how Flexera is integrating AI, you can explore their offerings here.

Terzo and Flexera are only two of the many players in this space. As I continue to investigate how AI is shaping the world, including SAM, I’m certain I’ll discover more examples of AI revolutionizing the world, for the good and bad.

Speaking of bad...

The Risky Business of AI

It doesn’t take a SAM professional to understand that with new technology comes new efficiencies. But, as Spiderman’s Uncle Ben wisely said, “With great power comes great responsibility.” AI risk management is becoming an essential component of AI usage. With the use of AI, it is important to keep an eye on:

  • Data Privacy
  • Bias and fairness
  • Security
  • And more!

While the risks of AI can seem daunting at times, it is important to recognize that by following effective risk management strategies, these risks can be mitigated. At SIE Consulting Group, we can help you navigate AI risks and manage them properly.

Excited to learn more? Don’t miss our upcoming AI Webinar where we will dive deep into the impact of AI on the federal government. Plus, stay tuned for an upcoming white paper on how to effectively manage AI risks.

Together, we can all become a little bit less n-AI-ve.