Machine Learning

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A Q&A with AWS’s Rahul Pathak on the advantages of transitioning your company to a data-driven enterprise.

Developing AI-enabled business models, managing corporate social responsibility, and growing digital ecosystems.

Leaders must focus on managing the gaps in AI skills and processes within the organization.

Companies and leaders must strive to build business models using three key components for growth.

CFOs need to lead AI technology decision-making — and they should start now.

Your AI strategy needs to be approached differently than regular technology strategy.

A successful AI-enabled workforce requires key hiring, training, and risk management considerations.

Preparing for AI’s next phase means prioritizing your talent pipeline and technology infrastructure.

A Q&A with AWS’s Michelle K. Lee on the challenges and advantages of adopting machine learning.

Insights for developing and executing AI strategy at the leadership, organization, and talent levels.

Companies are beginning to reboot their machine learning and analytics, disrupted by the global pandemic.

Ask these four questions to determine whether your AI system is really an AI solution.

Many businesses overlook a solution to the machine learning talent shortage: upskilling employees.

Business leaders must rethink data management to succeed with machine learning.

Social listening — analyzing what consumers say on social media — can serve as a treasure hunt map.

MIT SMR Winter 2020 examines workers’ emotions and education, tech dilemmas, and how best to transform.

New research offers companies a framework for managing successful country portfolios.

MIT SMR authors David Bray and R “Ray” Wang discuss how people-centered design principles can serve as a framework in AI implementation.

Companies already use data to make marketing decisions. Will deep learning enable a leap forward?