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S4 | Ep 47 | Bridging the AI Skills Gap with Anna Wang, Head of AI at Multiverse
Manage episode 441525939 series 2806428
In Episode 47, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Anna Wang, Head of AI at Multiverse, where they discuss current AI landscape and the key considerations to bridge the AI skills gap, which includes;
- Studying AI at Stanford
- Having her company acquired by Multiverse
- The combination of AI and behavioural science to evaluate skills
- If you’re serious about AI you have to be serious about data
- Building AI models than are 4x more accurate than interview processes
- Why there is no point in investing in AI if you’re not investing in the people that will use it
- The importance of investing in your people to make them effective at using AI as a tool
- Why LLMs are in a generalised state
- Why AI is lightyears ahead of where it was even 5 years ago
- The most common misconceptions about AI
- Why it’s unlikely that you can use AI out of the box
- Why people are leaning in too much to demo’s we see online
- How no one has yet been left behind yet, despite what people may believe
- What is preventing organisations in taking action with AI
- Why business leaders need to embrace an investment in learning
- The security and ethical fairness concerns that prevent action
- Why most businesses will be AI native in the future
- The consequences of inaction
- Why understanding the data that is powering your organisation is a good place to start
- The significance of the skills shortage in AI
- Why AI skills gaps is a multi-layered problem
- Why the speed of technological advancement is a challenge
- Why critical thinking and questioning skills are essential to get the most out of AI
- How team structures and operating models play a significant role
- Why AI infrastructure should be shared between data and tech teams
- Why whoever has the final decision on how AI is used should be incredibly business minded
- The importance of growing your experimental AI muscle
- Why urgency will play a major role in success
- The MAGE approach to training and upskilling organisations and people
- Training 16,000 people across 1500 organisations to make more impact at work
- The 2 vector that AI will impact in the next couple of years
- Tackling the fear from non-data or technology professionals
- The relationship between data culture and AI
- The importance of both data and AI literacy
Thanks to our sponsor, Data Literacy Academy.
Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.
If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.
At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.
From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.
We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.
Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.
201 episoder
Manage episode 441525939 series 2806428
In Episode 47, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Anna Wang, Head of AI at Multiverse, where they discuss current AI landscape and the key considerations to bridge the AI skills gap, which includes;
- Studying AI at Stanford
- Having her company acquired by Multiverse
- The combination of AI and behavioural science to evaluate skills
- If you’re serious about AI you have to be serious about data
- Building AI models than are 4x more accurate than interview processes
- Why there is no point in investing in AI if you’re not investing in the people that will use it
- The importance of investing in your people to make them effective at using AI as a tool
- Why LLMs are in a generalised state
- Why AI is lightyears ahead of where it was even 5 years ago
- The most common misconceptions about AI
- Why it’s unlikely that you can use AI out of the box
- Why people are leaning in too much to demo’s we see online
- How no one has yet been left behind yet, despite what people may believe
- What is preventing organisations in taking action with AI
- Why business leaders need to embrace an investment in learning
- The security and ethical fairness concerns that prevent action
- Why most businesses will be AI native in the future
- The consequences of inaction
- Why understanding the data that is powering your organisation is a good place to start
- The significance of the skills shortage in AI
- Why AI skills gaps is a multi-layered problem
- Why the speed of technological advancement is a challenge
- Why critical thinking and questioning skills are essential to get the most out of AI
- How team structures and operating models play a significant role
- Why AI infrastructure should be shared between data and tech teams
- Why whoever has the final decision on how AI is used should be incredibly business minded
- The importance of growing your experimental AI muscle
- Why urgency will play a major role in success
- The MAGE approach to training and upskilling organisations and people
- Training 16,000 people across 1500 organisations to make more impact at work
- The 2 vector that AI will impact in the next couple of years
- Tackling the fear from non-data or technology professionals
- The relationship between data culture and AI
- The importance of both data and AI literacy
Thanks to our sponsor, Data Literacy Academy.
Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.
If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.
At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.
From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.
We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.
Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.
201 episoder
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