Make it, buy it, or leave it: Strategies for efficient AI adoption

AI is everywhere at the moment and the pressure to keep up is real. Explore strategies and methods you can use to make your AI project a success, and apply them to your own business context.

Many AI initiatives still fail to deliver an appropriate Return on Investment (ROI). Often, this is due to missing information on possible strategies and prerequisites to address specific business problems with AI. Based on examples, this workshop introduces applicable strategies and methods identify the correct AI technology to solve your problem, determine whether your data is ready for your AI solution, and how to fill gaps in your data quality.

In hands-on working sessions, participants apply the explored strategies on their own real-world examples.

Learning Outcomes: After attending this course, you will be able to

• Apply methods to successfully propose, prepare and asses AI projects and their value for your business
• Assess whether your data is ready for AI applications

This workshop builds an ideal basis for the follow-up course "Make it, buy it, or leave it: ROI Analysis of AI projects"

Agenda & Content

Target audience, eligibility & prices

High-level managers, project managers and product managers that have to argue about the projected return of their AI investment

Entry level & prerequisites

Basic - no previous experience required. It would be helpful for the group exercises if you prepare a specific AI project that you want to work on.

Lecturer

Daniel Lehner (AI Factory Austria AI:AT)                        
Dr. Daniel Lehner works as expert in AI knowledge transfer at AI Factory Austria AI:AT. He also works as a consultant and trainer at TwinTech, helping companies to efficiently exploit the potential of digitalization through the use of artificial intelligence and digital twins. In addition to his work with various companies, he also draws on his many years of experience in researching digital twins and artificial intelligence at Johannes Kepler University in Linz.

Registration

Registration is required, the registration form can be found on top of this page in the menu on the left.

Please register with your official institutional email address to prove your affiliation.

You will get an automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders.

Following your successful registration, you will receive further information a few days before the course.

Please do not hesitate to contact us at training@ai-at.eu if you have any questions.

Waitinglist

After the number of registrations has reached its maximum or the registration form has been closed, you may want to send us an email (training@ai-at.eu) stating that you are interested to be put on the waiting list (vacancies may occur due to cancelations, etc.).

Modification, withdrawal & no-show policy

Your registration is binding. Please only register for the course if you are really going to attend.

You can update your registration data or withdraw your registration anytime before the registration form has been closed via the link "Manage my registration" which you can find at the bottom of your automatic email confirmation (subject starting with "[Indico] Registration").

Alternatively, or after the registration form has been closed, please inform us about your cancelation or any change in your registration data (especially your mobile-phone number) via email (training@ai-at.eu).

No-show policy: If you do not cancel and do not show up at the course you will be blacklisted and excluded from future training events.

Organizers

This course is organized by AI Factory Austria AI:AT.

Acknowledgements

AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).