I recently had the incredible opportunity to attend a webinar about the business value of AI, hosted by C4 Tech Services. The panelists included Brian Baker, Justin Grammens, and Matthew Versaggi, all experts in the AI and business strategy fields. The session was packed with valuable information, and I'd like to share some key insights with the Lorignite community.
My biggest takeaway: “AI unlocks doors we are not even able to imagine.”
As businesses undergo digital transformation, it's essential to remember that if you aren't leveraging AI, your competitors probably are. Implementing AI can be challenging due to concerns about job displacement and organizational resistance. However, emphasizing the "human in the loop" approach, where AI complements human work rather than replacing it, can help address these concerns.
One excellent example of AI implementation comes from Brian's company, vRad, which has integrated AI into their medical imaging practices. vRad's Radiology AI helps doctors quickly find serious health problems in medical images, allowing patients to get faster treatment and potentially saving lives. This large-scale application of AI is already benefiting patients, practitioners, and administrators, and it demonstrates the transformative potential of AI across various industries when properly integrated and scaled.
One interesting point Brian's raised was his company recently had an opportunity to expand its AI team but chose to focus on improving the classical IT stack to support AI initiatives.
Matthew, an AI veteran since the '80s, agreed that this is a common challenge; the integration of AI and classical IT is crucial for driving initiatives forward.
When considering AI projects, Justin Grammens, CEO at Lab651, reminds us that "when you have a hammer, everything looks like a nail." Identifying appropriate use cases is crucial for success. For example, at St. Thomas, professors were spending significant time reviewing business student presentations. AI was employed to automate repetitive feedback tasks like speed of delivery, hand gestures, and filler words, allowing professors to focus on higher-value interactions with students.
When planning an AI project, Matthew says keep these critical factors in mind:
Talent: AI engineers and other experts needed to build the project.
Data: Sufficient data is required to train and validate AI models.
Internal Knowledge: Frontline information is needed to train the model and validate its outputs.
Reward Structure: Align the project with business objectives to ensure it doesn't negatively impact performance metrics.
Infrastructure: Robust IT infrastructure is necessary to support AI initiatives.
AI projects are not a one-and-done endeavor. They involve building, scaling, and evolving over time to remain effective and up-to-date.
In summary, AI has the potential to unlock opportunities we can't even imagine yet. By understanding the challenges, focusing on appropriate use cases, and considering the key factors necessary for success, businesses can harness the power of AI to drive innovation and stay ahead of the competition.
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