You're about to start the test. To make sure that all participants complete the test from the same starting point, please note the following.1. 1Take your own organisation as starting point. If you work for an agency, please answer the questions for your organisation. Not that of a client.
- 2. Depending on your role we will ask questions about different themes like organisation, technology and impact.
3. If you still have doubts, please choose the answer that suits your organisation best. To complete the test, you must answer all questions.
After completing the test, you can see how your organisation scores on each theme and compared to other participants. The score is divided in four maturity levels. The DDMA AI Committee will give you advise per theme on how to reach the next level.
" data-category-boolean_deleted="0" data-category-date_created="2019-05-21 15:33:29" data-category-date_modified="2019-05-21 15:47:37" data-category-ddma_test_advice_with_1_points="
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Great that you are getting started with AI in your organisation. To grow to the next level, your next steps can be the following:
- Get a good understanding what AI really is and identify potential usecases for your organization
- Develop the skills yourself, get an external consultant and/or hire a data scientist (potentially graduation students)
- Then start working on it :). Start building and make experiments/proofs of concept (keep it simple)
- Include more people in the projects and educate people about what AI is and the potential of AI for the organisation. Think about more technical people, but also colleagues from the business. Perhaps it can help your organisation to hire some external expert to boost your projects
- Start organising your data analists or data scientists so they can help each other and make more impact. Perhaps train data analists to become data scientists
- Find a sponsor in senior management and get some innovation funding to fire up the engines
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Great, your organisation has already started with AI and reached level 2! Your next challenges may include:
- Getting more internal employees working on AI or taking the time to learn about the impact of AI
- Let business and science colleagues work together more frequently on Ai projects
- See if you can set-up data science teams in more business units to spread the knowledge
- Find sponsors in the regular marketing/ IT businesslines and have them make budget reservations for AI
- Think about predefined checks at the beginning of a new project and check ethical issues in your validation steps
- Try to explain your models on a customer level; "because of X, customer Y got this result". Or when you can't explain it, take an educated decision to (not) use an algorithm.
- Start considering legal and ethical aspects of AI projects, as wel as how you can explain how your models work
- You have run some AI experiments by now, and should be able to grasp the idea behind AI and the potential for your organization. Develop a vision where you want to go with AI inside your organization which supports in getting funding in place
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Based on your answers it seems you have organised AI pretty well. To take it to the next level, you can:
- Make sure the value of AI is seen from workfloor to boardlevel. Also, get as many internal employees from diverse backgrounds to learn about AI or be part of projects that include AI
- Get all layers of the organisation involved. Include higher management so heavily that they will initiate AI project themselves
- Make sure business and data scientists/engineers always work together as a multi-disciplinairy team on AI project
- Arrange budgets for your project, but on top of that find budget specifically to develop new capabilities for future value creation
- Incorporate legal and ethical aspects and colleagues in every step from start to finish. Consider using a legal and ethical board to review AI activities
- Challenge your teams to explain your AI models on customer level externally or estimate is as good as possible
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You are on top of your game! Based on your answers, it seems you are in the highest level. Now it is important to keep that level and perhaps upgrade on some of the aspects that still need improvement. If you haven't done this yet, this might also be the time to start sharing your knowledge and experience with other organisations. Together we can do greater things with data and AI!
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Additional tips for books to read, workshops to attend or blogs to follow:
- AI course by Jim Stolze (if you're completely new to AI)
- DDMA AI Afternoon Update > keep an eye on de DDMA newsletter. Sign up here. Please note that the majority of the newsletter is in Dutch, however some events are in English!
- Kevin Kelly Ted Talk
- Wait but why - Coursera
- Knowledge Management and Big Data in Business - edX
- Data Science Specialization - Coursera
- AI For Everyone - Coursera
" data-category-ddma_test_advice_with_2_points_details="
Additional tips for books to read, workshops to attend or blogs to follow:
- AI course by Jim Stolze (if you're completely new to AI or plan to bring non technical people to AI)
- DDMA AI Afternoon Update > keep an eye on de DDMA newsletter. Sign up here. Please note that the majority of the newsletter is in Dutch, however some events are in English!
- Kevin Kelly Ted Talk
- Wait but why - Coursera
- Visit meetups and seminars on AI (e.g. World Summit AI)
- TedX Decentralized AI: The Power and the Necessity
- Machine Learning for Data Science and Analytics - edX
" data-category-ddma_test_advice_with_3_points_details="
Additional tips for books to read, workshops to attend or blogs to follow:
- AI course by Jim Stolze (if you're completely new to AI)
- DDMA AI Afternoon Update > keep an eye on de DDMA newsletter. Sign up here. Please note that the majority of the newsletter is in Dutch, however some events are in English!
- Kevin Kelly Ted Talk
- Wait but why - Coursera
- Visit meetups and seminars on AI (e.g. World Summit AI)
- TedX Decentrelized AI: The Power and the Necessity
- Participate with your team in hackathons to boost your skills
- Visit the yearly cloud events (Micrsoft, AWS, GCP, etc) to stay on top of latest developments and to learn from other customers
" data-category-ddma_test_advice_with_4_points_details="
Additional tips for books to read, workshops to attend or blogs to follow:
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You are getting started on a great AI journey. To take the next step on your journey:
- Work on analyzing structured data from data dumps or databases. Ideally you would start organizing your data in a central database such that data scientists/analists have full access to all data
- Start training your models manually (ideally on a regular basis)
- Develop more computer science skills like git, structured programming, deployment, etc.
- Make sure that data scientists have powerful laptops, can use a departmental server for AI purposes or if possible have some budget for cloud AI solutions and/or VMs
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Great that you built up skills to start training AI models. To take it to the next level:
- Add more complex data sources like free text, images, audio content to enhance your business
- Explore more complex database systems/file systems such as Hadoop, S3 and distributed database solutions and update your models regularly with those systems
- Start to look into batch and streaming (online) Machine Learning models that can be updated in real-time. Also see if you can start a proof of concept on deep learning
- Look into scaling up the on-premise server to a cluster of servers such that models can be trained in parallel
" data-category-ddma_test_advice_with_3_points="
Great that you are already running AI models, to take the next step:
- Start analysing large complex unstructured data sets (e.g. video or a combination of sources)
- Find ways to easily deploy and automatically update your AI models on top of cutting edge solutions like s3, hadoop or distributed database solutions
- Start to look into Deep Learning models to boost the performance of your AI stack
- Consider to move to a cloud solution such that your AI services easily scale (also using hosted services has much less maintenance)
" data-category-ddma_test_advice_with_4_points="
You're at the top of the AI game. Stay in touch with the latest developments by following blogs on AI and following the developments the three biggest vendors for AI services: Google, Microsoft and Amazon. Also try sharing your knowledge with the broader AI community.
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Additional tips for books to read, workshops to attend or blogs to follow:
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Additional tips for books to read, workshops to attend or blogs to follow:
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Additional tips for books to read, workshops to attend or blogs to follow:
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Additional tips for books to read, workshops to attend or blogs to follow:
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Great that you are starting to use AI in your organisation. To take the next step;
- Start experimenting with AI to deliver value
- Choose some smaller and feasible AI pilot projects, and try to get those live in production
- Try to timebox projects, and start on something small that could deliver real value within half a year
- Focus on optimising or automating time consuming or high effort supportive tasks where you can bring value that was not possible without AI
" data-category-ddma_test_advice_with_2_points="
Great that you've started delivering value through AI! To take the next step:
- Try splitting up AI projects in smaller steps, so you can deliver value faster and get more into production
- Try looking at adding more new features or services that support the core business
- Start more AI projects on a wider range of business processes, to spread knowledge and gain more business process knowledge at the AI experts
" data-category-ddma_test_advice_with_3_points="
Great! You are doing really well making an impact with AI. To improve even further:
- Use AI to radically innovate and improve your core business or develop new products or services
- Try getting more of your pilots towards actual production phase, in which those projects deliver consistent business value
- Try looking at project organisation and input before a project starts, so you can timebox projects even better, and deliver value even faster
" data-category-ddma_test_advice_with_4_points="
You are at the top of creating impact with AI. Focus on keeping on top of the game, by continuously looking at what kind of new products or services could be delivered based on your data-collection, continuously optimising your processes, and keep making sure your pilots turn into critical business processes by picking the right projects.
And you can take the stage and share how you are organising what you are doing, and learn from other great organisation as well.
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Additional tips for books to read, workshops to attend or blogs to follow:
- Read blogs on making impact with AI
- Structuring Machine Learning projects - Coursera
- AI For Everyone - Coursera
" data-category-ddma_test_advice_with_2_points_details="
Additional tips for books to read, workshops to attend or blogs to follow:
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Additional tips for books to read, workshops to attend or blogs to follow:
" data-category-ddma_test_advice_with_4_points_details="
Additional tips for books to read, workshops to attend or blogs to follow:
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