Putting AI to Work

Welcome to Putting AI to Work – a program designed to accelerate the productive use of artificial intelligence (AI) in your organization.

If you are interested in learning more about CDL’s Putting AI to Work Program, please complete the Program Expression of Interest form.


Putting AI to Work is designed to empower organizations to boost productivity by 20% over two years through the application of artificial intelligence-based solutions. Over the course of 12 months, participants meet bi-weekly via Zoom to develop AI strategy plans and implement them.

Why Now?

Over the past two years, we witnessed a Cambrian explosion of off-the-shelf AI solutions that are now available for a wide range of applications across different industries. This shifted the challenge from finding something useful despite a scarcity of AI solutions to selecting from an abundance of options and implementing the most appropriate solutions quickly to deliver results.

Putting AI to Work helps organizations navigate this crowded landscape by accelerating the selection of AI solutions that best match their operational needs. Then, we guide a rapid iteration approach to implementation to ensure a timely delivery of tangible productivity gains.

AI Strategy

The program begins with a primer on developing a Phase 1 AI Strategy. Phase 1 is simple. Each direct report to the CEO develops a plan to harness the fewest number of AI solutions required to achieve a 20% productivity lift within their respective business unit or functional area.

This can manifest either as a 20% increase in the quantity or quality of output without raising costs, or as a 20% reduction in costs while maintaining the current level of output. The exercise begins by specifying a well-defined performance measure as the target for each unit’s efforts.

Each plan is designed to achieve productivity gains as swiftly and efficiently as possible. Thus, the strategy requires identifying the AI solution that offers the highest return on investment (ROI).

The longer-term Phase 2 AI strategy is not as simple. We introduce CEOs and their senior leadership teams to a framework for doing this in the latter half of the program. The framework is based on the best-selling book: Power & Prediction: The Disruptive Economics of Artificial Intelligence, authored by some of the co-creators of Putting AI to Work.

From Strategy to Implementation

Following the strategic groundwork laid in the Phase 1 AI Strategy, the Implementation phase of the program is focused on putting these plans into action. Here, we transition from theoretical planning to practical application, learning from peers, experts, and vendors to ensure that each of the selected AI solutions is implemented as smoothly and effectively as possible.

The implementation process begins by setting up the infrastructure needed to support AI-based solutions, followed by a structured rollout. Peers, experts, and vendors provide input and advice through the critical steps of integrating AI tools with existing systems, training staff on new processes, and monitoring progress against the specified performance measures.

To facilitate a successful implementation, the program provides introductions to experts for hands-on support, including regular check-ins and troubleshooting sessions. This ensures that any challenges encountered during the rollout are promptly addressed, minimizing disruption and maximizing the impact on productivity.

By the end of this phase, participants will have not only implemented their AI solutions but also started to see tangible improvements in efficiency and cost-effectiveness within their operations.

Application Examples

Putting AI to Work will provide participants with insights, support, and introductions to experts to accelerate the implementation of general off-the-shelf AI solutions as well as easy-to-use tools to build custom solutions.

The program will introduce participants to the most relevant off-the-shelf solution providers for common applications such as the 12 listed below:

AreaExample ApplicationsExample Performance Measures
SalesPredictive analytics for lead scoring, automated follow-upsIncrease in conversion rates, acceleration in sales cycle
Customer SupportChatbots, automated ticketing systemsPercentage of customer queries resolved without human intervention
Human ResourcesAutomated resume screening, employee sentiment analysisTime saved per hire, improvement in employee satisfaction scores
FinanceFraud detection algorithms, automated expense managementReduction in fraudulent transactions detected, decrease in processing costs
MarketingPersonalized content recommendations, campaign optimizationsIncrease in engagement rates, ROI on marketing campaigns
OperationsSupply chain optimization, predictive maintenanceReductions in downtime, improvements in supply chain efficiency
IT and CybersecurityThreat detection and response automationReduction in breach response times, number of incidents resolved automatically
Research and DevelopmentAccelerated product development cyclesReduction in time from concept to market
Quality AssuranceAI-driven quality inspection systems using computer visionDecrease in defect rates, increase in inspection speeds
Legal and ComplianceAutomated document review, compliance monitoringTime saved on document processing, reduction in compliance breaches
Supply Chain ManagementDemand forecasting solutions for better inventory managementReduced holding costs and minimized stockouts
Software DevelopmentAutomated code generation, bug detectionReduction in time from coding to production release, decrease in bugs found in production

In addition, when necessary, the program will introduce participants to easy-to-use tools to accelerate the development of custom solutions for problems that are unique to particular organizations (e.g., automated RFP responses for a roofing company that produces many commercial roofing proposals; automated behavior recommendations for a company that works with recently incarcerated individuals to reduce the likelihood of recidivism, automated solicitations of well-matched contract workers for a company that posts jobs on their platform).

Peer Sharing and Collaboration

Putting AI to Work is structured in cohorts to maximize the speed of learning and implementation. A cornerstone of the program is the emphasis on peer sharing and collaboration. As companies progress at different rates in their AI journey, those who lead in the implementation of specific applications (e.g., demand forecasting AI systems to enhance supply chain management ) will share their insights, experiences, best practices, and lessons learned. In turn, these companies will benefit from learning from other companies who are ahead in a different application domain (e.g., customer support AI systems).

Program Facilitator

Putting AI to Work is administered by the Creative Destruction Lab (CDL), a not-for-profit organization dedicated to fostering innovation and technological advancement in a manner that improves productivity and enhances the overall well-being of humankind. The CDL administered a similar cohort-based rapid learning, innovation, and deployment program for companies in 2021-2022 during the last big economic shock: Covid-19. The program was a great success with thousands of participants: The New York Times wrote about the first cohort here.

Join Us

Join Putting AI to Work to accelerate your organization’s use of artificial intelligence towards well defined performance targets. The program is structured into distinct cohorts, grouping similar types of organizations together to best address their specific needs: large enterprises, mid-cap companies, SMEs, government agencies, and not-for-profit organizations. At the same time, we ensure that companies that compete in the same market are not grouped together in the same cohort.

If you are interested in learning more about CDL’s Putting AI to Work Program, please complete the Program Expression of Interest form.