
Leading Change
Leading AI Is Still Leading
MIT Sloan Management Review’s fall 2023 issue includes a look at what it takes to lead artificial intelligence efforts.
MIT Sloan Management Review’s fall 2023 issue includes a look at what it takes to lead artificial intelligence efforts.
The fall 2023 issue of MIT Sloan Management Review examines innovation systems and strategies for business leaders.
With a modest amount of training, nontechnical employees can automate complex processes.
Research points to six practices leaders can use to overcome stakeholder resistance to automated negotiation technology.
This free webinar offers business insights about application programming interfaces (APIs).
Workers’ creativity will provide job security — even as robots take on parts of their roles.
This free webinar offers expert advice on adopting AI today and preparing for tomorrow’s challenges.
In this webinar, experts from Kaiser Permanente, Accenture, and SAS discuss business readiness for AI.
No-code software development platforms enable nontechnical teams to create and deploy simple apps quickly.
Practical strategies for hybrid work, linking good intentions to intentional actions, and Daniel Kahneman on “noise.”
A dedicated team can help maximize the utility — and competitive advantage — of automation systems.
The Me, Myself, and AI podcast delves into how automotive supplier Cooper Standard uses open innovation to leverage AI.
Companies upskilling their workforce are less likely to be caught flat-footed by broad tech changes.
Peer coaching plays a foundational role in developing human skills that technology cannot replace.
The skills challenge requires shifting initiatives and resources to where they are needed most.
A new article series explores opportunities to reimagine the future of workplace learning.
Companies that emphasize collaboration between AI and human workers are best positioned for success.
AI is a powerful tool for innovation when leaders communicate its benefits.
Despite advances in automation, good people and good techniques remain essential to manual work.
Shareholders and stakeholders, data science’s pandemic shift, and combating workplace discrimination.