The past few years have been marked by corporations announcing AI-centred initiatives and commitments to undertake large transformation projects.  
 
At Monolith, we worked alongside many large OEMs to implement machine learning solutions and have witnessed some of the key blockers to successful AI projects. 

 We are happy to deliver a new webinar on the trends in AI trust and what you should be aware of as we head into 2025. In this webinar, we will dive deep into why there are issues in trusting AI and whether those issues have a solid basis. We will draw comparisons to other technologies where using machine learning is already widely accepted, and highlight what measures are taken to decrease risks of AI implementation gradually. 

 As we near the end of 2024, we wanted to bring insights from where our CEO Dr Richard Ahlfeld thinks the industry is headed in terms of AI adoption for engineering.  

Webinar highlights  

• Outlook from Monolith's CEO Dr Richard Ahlfeld: Where does your level of trust leave you in terms of adopting AI for engineering?
  
  
• How do we learn to trust AI models? What are the key factors that lead large companies to accept and trust machine learning solutions
  
  
• What do different levels of trust look like? How even the most skeptical engineers can make use of machine learning and gradually build up trust
  
  
• Is AI still a black box? Why do we specifically call out AI a black box and not other tools which act similarly?
  
  
• What will AI adoption look like next year? What types of AI projects and successes are we hoping to see in 2025? 
  
  

  If you cannot attend the live session, we would still encourage you to register to receive the webinar recording.