What are the key benefits and risks associated with AI, ML, NLP, and CV in our industry? How can we leverage these technologies to stay competitive, and what are the potential risks if we do not?
What are the gaps in our data and AI/ML capabilities, and what steps are we taking to address them? Are we investing in the right areas, and how do we ensure we get the most value from our investments?
How can we build a data-driven culture within our organization? How do we start if we have not already done so? What critical skills and resources do we need to develop, and how do we ensure we have the right talent to support our data and AI/ML initiatives?
How can we ensure that our data and AI/ML initiatives are aligned with our overall business strategy and objectives? How can we measure the impact of these initiatives on our business performance, and how do we ensure that we prioritize the right initiatives?
How are we addressing the ethical and social implications of AI, ML, NLP, and CV? What measures are we taking to ensure that our use of these technologies is transparent, fair, and respectful of privacy and human rights?
How are we collaborating with other organizations, partners, academic institutions, and other industry leaders, to stay up to date with the latest advancements in AI, ML, NLP, and CV? How can we leverage these partnerships to accelerate our learning and development?
How are we communicating with our customers, employees, and other stakeholders about our use of AI, ML, NLP, and CV? How are we building trust and confidence in using these technologies and addressing concerns or questions that arise?