In this article, I identify extraordinary unmet learner needs and address them with a free offering: my business-oriented machine learning course series, which is designed to fulfill those needs – three vendor-neutral courses that deliver material critical for both techies and business leaders. If you or members of your team would benefit from taking the course series, see how to access it for free here. Your team needs it, your boss demands it, and your career loves it. But today's number-crunching craze tends to, tragically, overlook one key point: Of all the ingredients that are key to success with machine learning, the one that's most often missing isn't about technology or data. Many business leaders do know that machine learning can't succeed in optimizing operations without a proven management process guiding the project – but data scientists tend to focus on one thing and one thing only: hands-on practice with analytics.

For most organizations, artificial intelligence (AI) stirs a range of emotions, from optimism about increased business opportunities to confusion about its potential, to concerns about job displacement and potential bias. Yet, as indicated by a Forbes Insights survey of 700 C-level executives, despite these hesitations, AI presents many opportunities from greater product and service innovation to improved decision making. Presenting AI in terms that business leadership and the board will embrace requires elevating discussions above technical concepts and speaking to business benefits such as competitiveness, operational efficiency and revenue growth. For leaders looking to reap these benefits and advance AI within their firms, making a strong, solid business case around how AI will deliver is key, especially since the Forbes Insights research also shows that many leaders aren't entirely on board with AI just yet. While 45% say IT stakeholders express "extreme urgency" that AI be applied more widely within their firms, only 29% see that same sense of urgency among their C-suite (the percentage is even lower among boards of directors--10%).

The 5 AI basics every business executive needs to understand right now 2. NVIDIA and Canon Medical Systems announce partnership to accelerate the use of AI in healthcare 3. Auditors use AI to tackle accounting fraud 4. Risk managers can assess and limit the risk in M&A with AI 5. MIT and Stanford researchers develop AI system that processes sounds as well as humans 5. THE 5 AI BASICS EVERY BUSINESS EXECUTIVE SHOULD KNOW AI is not about technical analysis, it is about leveraging data and machine learning to drive business success. "Without business leadership, AI success in business will only be random and limited – which is why active, proactive involvement of business leadership is critical. READ ARTICLE 6. NVIDIA AND CANON MEDICAL SYSTEMS PARTNER TO ADVANCE HEALTHCARE Imaging providers worldwide may soon have access to a single source of AI- powered continuous updates for their existing install bases in the form of a single, virtual supercomputer. READ ARTICLE 7. AUDITORS USE AI TO TACKLE ACCOUNTING FRAUD Accounting fraud has long eaten into the revenue of some businesses, but auditors are enlisting a new defensive tool: artificial intelligence. A typical organization can lose 5 percent of its annual revenue to fraud, according to an estimate from the Association of Certified Fraud Examiners. Businesses are putting AI on the task of anomaly detection in an effort to staunch losses. READ BLOG 8. RISK MANAGERS CAN ASSESS AND LIMIT RISK IN M&A WITH AI A company that has joined another is almost always saddled with data that's not so easy to organize and categorize. Most obviously, GPUs bring speed to the equation – and speeding up the process translates to identifying -- and mitigating -- risks sooner. "We're just trying to give users a tool to learn about data," said Jonathan Bailey, vice president of analytics at Congruity360. READ BLOG 9. RESEARCHERS DEVELOP AI SYSTEM THAT PROCESSES SOUND LIKE HUMANS The method, which is the first model of its kind, can replicate listening tasks such as identifying a musical genre or identifying words. The researchers built the model to shed light on how the human brain may be performing listening tasks. The hope is that it's learning something general, so if you present a new sound that the model has never heard before, it will do well, and in practice that is often the case. The 5 AI basics every business executive needs to understand right now 2. NVIDIA and Canon Medical Systems announce partnership to accelerate the use of AI in healthcare 3. Auditors use AI to tackle accounting fraud 4. Risk managers can assess and limit the risk in M&A with AI 5. MIT and Stanford researchers develop AI system that processes sounds as well as humans "Without business leadership, AI success in business will only be random and limited – which is why active, proactive involvement of business leadership is critical.

This article was written by Sudhir Jha (Senior Vice President & Global Head of Product Management and Strategy), and was edited and created in partnership with Infosys. This article is based on insights from Infosys' recent Leadership in the Age of AI research report. View the report itself to learn more, and to read about the research methods used. As businesses around the world continue to produce new use cases for artificial intelligence (AI), the technology's ability to foster or eliminate a level playing field creates a growing concern about its overall power and influence on the future workforce. While most agree AI holds vast potential to unlock discoveries we haven't yet conceived, for many, AI strikes concerns over job displacement, economic instability and skills shortages.