Data reveals the C-suite recognizes that technical debt — the “price” companies pay for short-term technological fixes — hinders their ability to innovate and adapt in the digital age. One strategy to combat technical debt? Digital decoupling.

Companies are adopting artificial intelligence at an accelerated pace — and learning that developing and deploying AI is not like implementing a standard software program. Before diving into AI systems, companies should consider three principles that can greatly improve the chances for a successful outcome. First, they need to recognize that humans and machines are in this together. Second, they need to teach the AI systems with a lot of data. And third, they need to continually test what the systems have learned.

The danger in using artificial intelligence to expedite inefficient legacy processes is that the technology may prolong the life of systems that limit competitive advantage.

In Part 5 of our eight-part video series, we look at production steps in digital additive manufacturing.

In Part 4 of our eight-part video series, we look at how digital simulation technologies like finite element analysis (FEA) make product testing more efficient and cost-effective in both short- and long-term contexts.

In Part 3 of our eight-part video series, we explore the technologies used for topology optimization and the role they can play in improving component and product performance.

In Part 1 of our eight-part video series, we explore the real power of the digital thread, which lies not just in a “cradle-to-grave” virtual rendering of the manufacturing process, but also in the possibility of taking the lessons learned from analyzing product performance and applying them to future generations of the manufacturing process and product design.

Our eight-part video series explores how integrated digital technologies can transform business.

Managers may wonder what sets AI apart from all the other highly touted technologies that may (or may not) live up to their hype. The key difference: We now have sufficient processing power to make good on AI’s promise.

Poor communication between managers and technical experts is an obstacle to technology innovation that literally has been present for centuries. To overcome these issues, leaders need to absorb three key lessons about how to manage the inherent tensions between defining technical requirements and achieving valuable business outcomes.

A new global study finds several new categories of human jobs emerging. These roles are not replacing old ones. They are brand-new positions that complement the tasks performed by AI machines and will require skills and training that have never before been needed.

The 2017 Data & Analytics Report by MIT Sloan Management Review finds that the percentage of companies deriving competitive advantage from analytics increased for the first time in four years. Incorporating survey results and interviews with practitioners and scholars, the report finds that companies’ increasing ability to innovate with analytics is driving a resurgence of strategic benefits from analytics across industries. The report is based, in part, on MIT SMR’s seventh annual data and analytics global survey, which includes responses from 2,602 business executives, managers, and analytics professionals from organizations located around the world.

With the benefit of digital technologies, companies are using Big Data to identify supply chain risks and create early warning systems with much greater speed and precision. However, the ability to respond to these signals hasn’t advanced at the same pace.

As digital technologies evolve, managers and employees will need to learn three important skills: partnering with new digital “colleagues,” creating a mindful relationship with omnipresent digital technologies, and developing empathy for the varying technology preferences of their human coworkers. Organizations, for their part, will need to design processes to support these efforts, and managers will need to be both flexible and thoughtful in how they respond.

What’s happening this week at the intersection of management and technology: how to avoid digital black swans; partnering with early-stage startups; the trouble with wearables.

Artificial Intelligence is about to transform management from an art into a combination of art and science. Not because we’ll be taking commands from science fiction’s robot overlords, but because specialized AI will allow us to apply data science to our human interactions at work in a way that earlier theorists like Peter Drucker could only imagine.

The right open innovation strategy can yield performance benefits — but first your company needs to overcome “not-invented-here” and “not-sold-here” attitudes.

For manufacturers and service companies alike, the ability to sell integrated solutions requires completely new organizational structures and capabilities.

The benefits of Web services will be profound, but not easily or quickly obtained. Building application-to-application links will require not only excellent technologists but skilled managers and leaders as well.

For managers seeking to abandon follow-the-pack IT investment, the author offers the example of Inditex Group, a clothing manufacturer in northwestern Spain, best known for its Zara stores. Inditex demonstrates that a company can select, adopt and leverage IT while spending very little on it. He lays out five general principles that underlie Inditex”s remarkable success with targeted technology spending.