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3 AI Mistakes to Avoid in a Recession

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3 AI Mistakes to Avoid in a Recession

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While the current economic outlook may be worrying, it doesn’t mean that companies can slow down on their AI strategies. That said, there are right ways and wrong ways for executing such strategies when the economic outlook is gloomy. Building on nearly a decade of experience working on the front lines of AI in the enterprise, this presentation illustrates three risks and three strategies for overcoming those risks when advancing an AI strategy in a bearish environment.

While the current economic outlook may be worrying, it doesn’t mean that companies can slow down on their AI strategies. That said, there are right ways and wrong ways for executing such strategies when the economic outlook is gloomy. Building on nearly a decade of experience working on the front lines of AI in the enterprise, this presentation illustrates three risks and three strategies for overcoming those risks when advancing an AI strategy in a bearish environment.

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3 AI Mistakes to Avoid in a Recession

  1. 1. ©2022 Dataiku, Inc. dataiku.com contact@dataiku.com
  2. 2. 3 AI Mistakes to Avoid in a Recession 24 November 2022
  3. 3. ©2022 DATAIKU, INC [ 3 ] What is Dataiku and who am I? Dataiku Dataiku is the platform for Everyday AI, enabling business and technical teams to work together to produce exceptional business results. Kurt MUEHMEL Everyday AI Strategic Advisor 8 years at Dataiku, always working with our now 500+ customers
  4. 4. ©2022 DATAIKU, INC Let’s be honest: the current situation is worrying! We need to avoid magical thinking, it’s time to be pragmatic. Let’s be careful and avoid some common mistakes. ©2022 DATAIKU, INC 3 Mistakes to Avoid in a Recession Don’t pursue the wrong use cases 01. Don’t forget that the value of AI goes beyond the use case 02. Don’t let reality escape you: control your spending 03. [ 4 ]
  5. 5. ©2022 DATAIKU, INC Mistake 1: Pursuing the wrong use cases What is the problem? You need to improve your success ratio for a new AI initiative. The Magical AI Success Formula In recessionary times, it is unlikely that you will be able to increase your resources and to be able to do more work. Success = Success Ratio ✕ Work [ 5 ]
  6. 6. ©2022 DATAIKU, INC Mistake 1: Pursuing the wrong use cases What is the solution? Select use cases that will demonstrate new advances Focus on the highest performing model Seek the highest- performing infrastructure DO NOT Select use cases that will help other departments control costs Focus on the most relevant model to the business problem Adapt the infrastructure to the business needs of the end beneficiaries DO Including a broader range of stakeholders and, most importantly the lines of business whose process we are impacting, in every step of the AI development process. Democratization! [ 6 ]
  7. 7. ©2022 DATAIKU, INC [ 7 ] Mistake 2: Not controlling spending What is the problem? It is time to be realistic and pragmatic. Times are different and it’s going to be more difficult in the coming months and maybe years. The spigot of “innovation funding” will likely dry up. We’ve discussed about getting more out of your people, how to get more out of your data assets?
  8. 8. ©2022 DATAIKU, INC [ 8 ] Mistake 2: Not controlling spending What is the solution? Governance! Governance is about more than just controlling who has access to what. You need to build process to enforce sharing and reuse. Strong AI Governance ensures that you have the tools needed to reuse and share assets, while maintaining necessary controls
  9. 9. ©2022 DATAIKU, INC [ 9 ] Mistake 3: Forgetting value beyond the use case What is the problem? Recessionary times will shift the focus from revenue generation to cost savings. You need to think like a resource-constrained start-up. Every minute counts. How can you get your new initiative into production as quickly as possible?
  10. 10. ©2022 DATAIKU, INC [ 10 ] What is the solution? Accelerate! Every opportunity to reduce your time to market is worth exploring. If you don’t absolutely need to build from scratch, don’t! Example Became Dataiku users in the context of 2020 Initial Challenges Quickly deliver marketing use cases for which business expectations were high Scaling out AI deployment in a traceable, transparent, and collaborative manner Getting all the available data out of silos and into a unified, analytics-ready environment Mistake 3: Forgetting value beyond the use case
  11. 11. ©2022 DATAIKU, INC [ 11 ] Delivering accelerated AI journeys with Dataiku Solutions Jan 2020 Dataiku customer! Sept 2021 Dataiku Solution Market Basket Analysis The example of M&M Direct, a British e-commerce company
  12. 12. ©2022 DATAIKU, INC [ 12 ] Benefits Eased analysis of association rules at various granularity: country, product, … Business empowerment (merchandising, e-commerce) with analytics thanks to pre-built web-app Use-case robustness AI delivery acceleration: 2 hours for end-to-end implementation Business Objectives Optimize product assortment and recommendation strategies through association rules based on co-purchasing frequencies. Market Basket Analysis INPUTS sales figures, customer actions on the website OUTPUTS Recommendation score per customer for certain products, and more... Plug-and-Play Solution Structured Flow Ready-to-use Dataiku APP. User-Friendly Dashboard Delivering accelerated AI journeys with Dataiku Solutions The example of M&M Direct, a British e-commerce company
  13. 13. ©2022 DATAIKU, INC [ 13 ] Jan 2020 Dataiku customer! Sept 2021 Dataiku Solution Market Basket Analysis Nov 2021 Dataiku Solution RFM-enriched Customer Lifetime-value The example of M&M Direct, a British e-commerce company What does it mean for our customers
  14. 14. ©2022 DATAIKU, INC [ 14 ] Benefits Strong enhancement to previous home-made version thanks to clustering approach. Time-to-value thanks to fully customizable template approach. Revised focus in advertising spending, customer care and more. Business Objectives Leverage improved understanding of customer lifetime value to optimize various processes starting from advertisement spending. RFM Enriched Customer Lifetime Value INPUTS transactional data per purchase, product characteristics and use (optional) OUTPUTS RFM score, customer segment, expected lifetime value, most bought product for high CLV Template Analytical APP Structured Flow Ready-to-use Dataiku APP. User-Friendly Dashboard The example of M&M Direct, a British e-commerce company Delivering accelerated AI journeys with Dataiku Solutions
  15. 15. ©2022 DATAIKU, INC In real life: M&M Direct The case of a British e-commerce company This solution allowed us to accelerate topics that simply could not fit into our busy roadmap. The implementation only took a few hours, and we are now ready to launch a marketing campaign powered by this solution. Ben POWIS Head of Data Science at MandM Direct ©2022 DATAIKU, INC Robustness Business Empowerment AI impact enhancement Time-to-value [ 15 ]
  16. 16. ©2022 DATAIKU, INC [ 16 ] Let’s be honest: the current situation is worrying! 3 Mistakes to Avoid in a Recession Don’t pursue the wrong use cases Don’t let reality escape you: control your spending Don’t forget that the value of AI goes beyond the use case 3 Recommendations for Success Democratize your process Govern your process and reuse your assets Accelerate your AI development workflow
  17. 17. Thank You ©2022 Dataiku, Inc. dataiku.com contact@dataiku.com

Editor's Notes

  • Abstract: While the current economic outlook may be worrying, it doesn’t mean that companies can slow down on their AI strategies. That said, there are right ways and wrong ways for executing such strategies when the economic outlook is gloomy. Building on nearly a decade of experience working on the front lines of AI in the enterprise, this talk will illustrate three risks and three strategies for overcoming those risks when advancing an AI strategy in a bearish environment.
  • Dataiku was created in February 2013 with 4 co-founders in France. First customers by the end of 2013. Dataiku releases a major version roughly once or twice a year.

    We’ve had several successful rounds of funding and are now valued at over a billion dollars and identified as a unicorn. We are at over 700 employees all over the globe. And have been acclaimed as one of the top companies to work for by Forbes, Glassdoor and Inc.

    Dataiku hosts the EGG thought leadership conferences in most major cities, currently called EGG On Air. We work with various charitable organizations through our not-for-profit arm Ikig.ai.
  • Dataiku was created in February 2013 with 4 co-founders in France. First customers by the end of 2013. Dataiku releases a major version roughly once or twice a year.

    We’ve had several successful rounds of funding and are now valued at over a billion dollars and identified as a unicorn. We are at over 700 employees all over the globe. And have been acclaimed as one of the top companies to work for by Forbes, Glassdoor and Inc.

    Dataiku hosts the EGG thought leadership conferences in most major cities, currently called EGG On Air. We work with various charitable organizations through our not-for-profit arm Ikig.ai.

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