AI offers a powerful tool for digital transformation, but businesses need to address data infrastructure challenges and ensure collaboration between business and technical teams to succeed. AI excels at solving specific problems and enhancing decision-making, but it's not a replacement for human judgment, especially in complex situations.
On November 9th, 2021, PlugANDPlay hosted Skan's fireside chat on “A Practical Overview of Artificial Intelligence for Business Leaders” which was led by Avinash Misra, CEO and Co-Founder of Skan. The chat featured senior leaders and executives with decades of AI experience across digital transformation and process excellence:
The panel had an insightful conversation about how AI is no longer the stuff of science fiction and is now one of the top trends being embraced by enterprise business leaders around the globe
Watch the full video below or read on to see our top 4 takeaways from this insightful discussion.
The Top 4 Insights from “A Practical Overview of Artificial Intelligence for Business Leaders
AI is experiencing a “magic moment”
In the past few years, many factors, including the pandemic, have created a need for digital transformation. On the forefront of this change is AI. As Sanjay mentioned “the largest driver of transformative value” for many enterprises is the ability to unlock the value of their internal data. The combination of these macro trends, business needs, and technology advancements are coming together to create a magic moment for AI to drive this transformation.
The small dataset problem
Despite being in a “magic moment,” AI is not magic. It requires data to be effective. For business leaders to be able to take advantage of new AI technologies requires investment and maturity on the data side. Many organizations are not there yet and business leaders need to make sure that they are coordinating with the right technical teams to ensure that the infrastructure is in place to render the AI successful.
Deployment is the key to solving real problems
The real challenge is moving AI out of the lab. Business leaders need to have the right infrastructure and support from their technical teams in order to accomplish this. As Sanjay stated, "AI is one component that can deliver great results, but it needs to be done in the context of a larger engineered application" that encompasses data ingestion, modeling, and governance.
The next evolution of AI is augmented intelligence
AI is best applied to solve specific tasks and challenges. It doesn't replace human judgment and reasoning where uncertainty is involved and complex decision making is required. However, it can help business teams and organizations make better decisions faster. The next evolution of AI is accelerating this decision making where machines and humans are working in tandem.