Zachary Jarvinen

Artificial intelligence offers significant benefits for a broad range of markets. The most noticeable is optimizing the workforce by increasing their efficiency and reducing the burden of manual tasks. AI is good at automating things you might feel bad about asking someone else to do, either because it is tedious, such as reading through reams of reports, or dangerous, such as monitoring and managing workflow in a hostile environment.

Chances are good that you’ve sent an email to a customer service department at one point or another. Perhaps your order was late, items were damaged in shipping, or you needed to know how to initiate the return process. You may have found that while some companies are prompt in sending a reply and resolving your issue, you may not hear back from others for days.

An intelligent recommendation system analyzes the available information to produce a detailed, individualized picture of each customer and make predictions about their preferences and behavior, specifically their buying propensity.Many offers are irrelevant to consumers or may even strike the wrong note. For example, you aren’t putting your best foot forward by recommending a romantic getaway to someone in the middle of a messy divorce, or by listing the benefits of retirement community units to someone under 30.

Business organizations look to professional services firms to offload existing processes such as payroll, claims processing, and other clerical tasks. Consequently, rather than push the innovation curve as early adopters of emerging technology, professional services firms have traditionally followed well-established procedures and used conventional tools.

They say if it ain’t broke, don’t fix it, but anyone with high-value assets, whether a fleet of bucket trucks or drilling rigs, knows preventive maintenance is much more effective than performing repairs reactively. Servicing equipment before it fails reduces costly downtime and extends its lifespan, thus stretching your resources as far as possible.

Recently Gartner analyst Nick Heudecker generated a firestorm of debate when he said a previous Gartner statistic that reported 60 percent of big data projects fail was too conservative and that an 85 percent failure rate is more accurate. Either way, it’s a daunting statistic.One way to avoid becoming a statistic is to approach your AI journey using an industry-proven model — the machine learning development life cycle.

In addition to not pursuing profit, government agencies and nonprofit organizations often work with constrained budgets and limited resources, and AI can help with both. Government In 2002, the world generated 5EB (exabytes) of data. That is the equivalent of a 4-quadrillion (18 zeroes) page text document or 5 billion hours of high-definition YouTube videos.

The high-value applications of AI are built upon a hierarchy of competencies. This figure shows the hierarchy of competencies required to use artificial intelligence. Hierarchy of AI competencies. Data collection Data collection is the foundation of the pyramid, the stage where you identify what data you need and what is available.