Artificial Intelligence - what makes sense?
Striped Giraffe Innovation & Strategy
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According to Gartner , artificial intelligence is one of the top 3 investment areas for CIOs in EMEA in 2024. This is quite understandable because AI can achieve high added value if it is fed with the right data.
Several industries have already developed a large number of use cases. In this newsletter, you will find some information on the pharmaceutical, automotive, and insurance sectors.
Enjoy!
AI in pharma
Identifying high-value use cases is the top challenge hampering the adoption of artificial intelligence by life sciences companies, as indicated by almost a third of respondents to the Deloitte survey.
They also pointed to multiple technological challenges associated with AI implementations, including poor-quality data, siloed data systems, integrating AI into legacy systems, and choosing the right technology.
On the other hand, respondents identified several operational challenges such as difficulty integrating AI into the organization, managing AI-related risks as well as finding talents with industry expertise and AI skill sets.
Explore more insights about leveraging AI in the life sciences, pharma and healthcare industries in our free booklet: https://bit.ly/AI-pharma
AI in automotive
Generative AI is ushering in a new era in the automotive industry, revolutionizing almost every area from design, engineering, and manufacturing to marketing, sales, maintenance, and customer support.
Recently, Toyota Motor Corporation unveiled its new generative AI technique that significantly enhances the capabilities of vehicle designers by incorporating engineering constraints into AI-generated models.
Currently, designers can use publicly available text-to-image generative AI tools as an early step in the creative process. With the new technique, they can add initial design sketches and engineering constraints into the process, shortening the iterations needed to reconcile design and engineering issues.
Constraints like drag (which affects fuel efficiency) and chassis dimensions like ride height and cabin dimensions (which affect handling, ergonomics, and safety) can now be implicitly incorporated into the generative AI process.“
Generative AI tools are often used as inspiration for designers, but cannot handle the complex engineering and safety considerations that go into actual car design,” said Avinash Balachandran, Ph.D. from Toyota, whose team worked on the technology. “This new technique combines Toyota’s traditional engineering strengths with the state-of-the-art capabilities of modern generative AI.”
Find more use cases of AI in automotive in our booklet bit.ly/AI-automoto
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AI for the insurance sector
?? CB Insights unveiled the Insurance AI Readiness Index — a ranking of 50 major insurance companies across the Americas and Europe. This index evaluates companies based on their capacity to innovate in AI and execute AI initiatives.
????The ranking shows how the top 50 insurance companies (subsidiaries included) are prepared to adapt to a rapidly evolving AI landscape across 2 key pillars: innovation and execution.
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The innovation score measures an insurance company’s track record of developing or acquiring novel AI capabilities. This score is based on CB Insights data including acquisitions, deal-making activity, and patent filings for each player.
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The execution score measures an insurance company’s ability to bring AI-powered products and services to market, as well as deploy AI internally across corporate functions. This score is based on CB Insights data including business relationships (partnership & licensing agreements), product launches, and earnings transcripts.
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Cigna Healthcare emerges as a frontrunner in AI readiness, attributed to its strong track record in AI innovation. Notably, Travelers and Munich Re secured top positions in the index, underscoring their commitment to embracing AI-driven solutions.
The emergence of GenAI-powered products is a prominent trend among industry leaders, with a significant number of companies focusing on operational enhancements like claims processing and document summarization.
Overall, the Insurance AI Readiness Index serves as a valuable benchmark for understanding how insurance companies are leveraging AI to stay competitive in a rapidly evolving market landscape.
? Browse the full list of 50 companies here: https://bit.ly/3vh1rmj
Our related resources:
?? E-book “Digitalization in the financial sector”: https://bit.ly/FinEbook-EN
?? Booklet “AI in finance and insurance”: https://bit.ly/AI-fintech
?? Blog article “Top 7 challenges of digitization in the financial sector”: https://bit.ly/FinDigital
For further information on these and other data topics, please contact us at [email protected] .
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7 个月This post might just be the definition of "valuable content" on LinkedIn. Fantastic synthesis of research from Gartner and Deloitte, combined with personal insights and experiences. We all feel that AI has the potential to finally be the game changer in the market. However, as with many other innovative technologies, it's crucial to find areas where its implementation brings "added value" and to ensure that the conclusions AI reaches are based on quality data. Striped Giraffe Innovation & Strategy - Are any of you observing an increased demand for data quality improvement services?