AI Articles and Analysis about Enterprise resource planning

One of the many concerns that business leaders have around automation is how they're going to adapt their workforce to new technology. The digital age has brought a rapid shift in the skillsets employees need to go about their jobs effectively, leaving little time for business leaders to come up with strategies for how to reskill and retrain their employees, prevent their companies from drawing disdain from the public, and how to compete with their peers.

We spoke with David Carmona, the GM of Artificial Intelligence at Microsoft about his approach to AI ROI with the enterprise clients he works with at Microsoft. The biggest takeaway from this episode comes right at the beginning. David talks about how to think about artificial intelligence ROI in the long-term and the near-term.

We spoke with Jonathan Ross, CEO and founder of Groq, an AI hardware company, about software defined compute. This interview is part of a series we did in collaboration with Kisaco Research for the AI Hardware Summit happening in Mountain View, California on September 17 and 18. 

We set out to create a report that would be particularly useful for executives and business leaders who are looking to get started with an AI initiative, as well as IT and management consultants who want to competently and effectively guide their clients through AI adoption.

Although there are established use-cases for AI applications in the business world, the claims that AI vendors make about returns from their software are often exaggerated. What is also not apparent amongst the AI hype is that adopting AI and machine learning is far more challenging than it might seem.

This week we speak with David Carmona, General Manager of AI at Microsoft. Carmona discusses how redefining a business process is a very different kind of AI adoption project than working on something that is horizontal.

Investment in AI by banks and financial institutions for risk-related functions such as fraud and cybersecurity, compliance, and financing and loans has grown dramatically in the last half-decade compared to customer-facing functions.

AI and machine learning have had successful applications in the financial sector even before the entry of the mobile banking ecosystem. AI is being used to leverage insights from data for financial investing and trading, wealth management, asset management, and risk management.