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AI leaders on the organizational level | AI news watcher’s blog | Partner voice

Tuesday, November 12, 2024
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6 things high-achieving orgs do to wring real value from AI

What makes an organization an AI leader? Demonstrating success in one of two pursuits. 

Either the org has a.) developed cutting-edge AI capabilities and is already using them to consistently generate substantial value. Or it has b.) put an AI strategy in place and is starting to generate value from the effort.

Combined, those two groups comprise 26% of the field in a recent survey of 1,000 organizations around the world. The “a” group was just 4%, the “b” group the other 22%. 

The remaining 74% “have yet to show tangible value from their use of AI,” write the authors of the survey report. “These categorical distinctions are important because leaders far outperform the others.”

The report was authored by 12 subject matter experts at Boston Consulting Group, aka BCG, which also commissioned the survey. The authors name six things that AI leaders “do differently.” These are: 

1. They focus on core business processes as well as support functions. 

“A common misconception is that AI’s value lies mainly in streamlining operations and reducing costs in support functions,” the authors learned via the survey. “In fact, its greatest value lies in core business processes, where leaders are generating 62% of the value.” More:  

‘Leveraging AI in both core business and support functions gives these companies competitive advantage.’

2. They are more ambitious. 

Three-quarters of the most forward-looking companies “focus on company-level innovation core to the business,” BCG reports. By contrast, only 10% of other companies do so—“and if they leverage AI at all, it is mainly for productivity.” More: 

‘Leaders make twice the investment in digital, twice the people allocation and twice the number of AI solutions scaled.’

3. They invest strategically in a few high-priority opportunities to scale and maximize AI’s value. 

Data on AI adoption shows that leaders pursue, on average, only about half as many opportunities as their less advanced peers, the authors write. “Leaders focus on the most promising initiatives,” they add, “and they expect more than twice the ROI in 2024 that other companies do.” More: 

‘In addition, leaders successfully scale more than twice as many AI products and services across their organizations.’

4. They integrate AI in efforts both to lower costs and to generate revenue. 

“Almost 45% of leaders integrate AI in their cost transformation efforts across functions, compared with only 10% of non-leaders,” BCG found.   

‘More than a third of leaders focus on revenue generation from AI, compared with only a quarter of other companies.’

5. They direct their efforts more toward people and processes than toward technology and algorithms.

Leaders follow the rule of putting 10% of their resources into algorithms, 20% into technology and data and 70% into people and processes, the authors write. More: 

‘Our data shows these are the key capabilities underpinning success.’

6. They have moved quickly to focus on GenAI. 

Leaders use both predictive AI and GenAI, and they are faster in adopting GenAI, the authors share. This is key, they note, because: 

‘GenAI opens opportunities in content creation, qualitative reasoning, and connecting other tools and platforms.’ 

Read the full report.

 

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Nabla Joins the Coalition for Health AI (CHAI) to Advance AI Governance in Healthcare - Nabla is joining forces with the Coalition for Health AI (CHAI), a diverse consortium of more than 3,000 organizations, including health systems, technology developers, patient advocates, and academic institutions, dedicated to promoting responsible AI practices in healthcare.

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Industry Watcher’s Digest

Buzzworthy developments of the past few days.

  • Where do you live? How susceptible is your neighborhood to environmental toxins and street crime? And how easy or difficult is your access to primary care and cancer screenings? These are the kinds of real-world variables AI algorithms should be crunching when assessing an individual’s social determinants of health. The goal should be to look “beyond traditional socioeconomic parameters and create tailored healthcare plans to eliminate health disparities.” That’s the view of Mayo Clinic President John Halamka, MD. He presented Mayo’s experiences with AI vis-à-vis “sustainable development impact” at a recent meeting of the World Economic Forum. More on his talk here
     
  • Healthcare payers favor software that helps their companies personalize member experience and engagement. The finding is from a survey of 450 payer executives and managers conducted by the healthcare SaaS company HealthEdge. Respondents collectively identified as key areas of investment AI solutions (16%), care management workflow solutions (13%), payment integrity solutions (13%) and member-facing mobile apps (12%). The survey report’s authors comment that such investments can improve consumer engagement while reducing “payment friction.” 
     
  • To date, all AI-enabled medical devices cleared by the FDA use locked algorithms. This means the models are not continuously learning or automatically evolving in the field. The strength of locked AI is its consistency and predictability. However, locked algorithms “can become less clinically valuable over time due to evolutions in clinical practice, changes in patient populations and other factors that contribute to ‘drift.’” So notes AdvaMed in a new overview of AI in healthcare. Human-in-the-loop AI “can help to ensure accuracy and ethical oversight,” the authors point out, “but can slow down decision-making processes or intervention.” Full paper available here
     
  • AI-powered virtual reality is so attractive to student nurses that it may need to be reined in. At least, that’s the case at the UNC Greensboro School of Nursing. There the applications for the technology include simulated bedside encounters with patients. “The use of AI was mind-blowing to me at first,” says nursing student Richelle Hensen. “AI thinks creatively and can illuminate new avenues in nursing studies.” Hensen is foresighted enough to recognize a potential downside in the technology’s power. “I do fear,” she says, “that it could be used too much.”
     
  • One state’s legislators are putting healthcare AI under the microscope. The state is Georgia. The interrogators include members of both major political parties. “Are [patients] going to really, truly have the ability to say, ‘I don’t want that; I don’t want to be monitored [by AI]?” asks a Republican. And what about cultural or ethnic bias arising from AI algorithms? adds a Democrat. The debate went down at a meeting of the Peach State’s House and Senate AI committees last week. Answering questions and concerns was Alistair Erskine, chief information and digital officer at Emory Healthcare. He explained that healthcare providers can analyze patient outcomes and look for opportunities to deracialize data, but he also acknowledged that AI is not perfect. Coverage by Rough Draft Atlanta
     
  • Around the world, policymakers should avoid reinventing the wheel just for AI. That’s the stance of Divya Srivastavad, PhD, of City St George’s University of London in the U.K. “International forums offer a space for sharing collective learning to identify policy responses, joint problem solving and coordination to mitigate barriers,” she writes in a paper published by LSE Public Policy Review. “AI has become the use case for ongoing collaboration and learning in global health. Indeed, this brings to the fore a notion articulated almost two decades ago around a model for continuous learning by the National Academy of Medicine—learning health systems—an approach that resonates when it comes to AI in health and is more pressing now than ever before.” Read the whole thing
     
  • ‘Is AI in healthcare a timely solution or a ticking time bomb?’ If you were to ask me that question, I’d want to ask back: Can the answer be a “both/and” rather than an “either/or?” Be that as it may, a young writer fleshes out the deciding factors in a piece posted at HackerNoon. There the writer uses a pen name, Juxtathinka, but elsewhere she’s not secretive about her real identity: Gimbiya Galadima, a medical student and creative writer from Nigeria.
     
  • A startup has developed an AI-powered toilet camera that analyzes human waste to provide ‘valuable health insights.’ The Texas-based company is creatively named Throne. Covering the development for Daily Galaxy, journalist Samir Sebti points out: “It is crucial for potential users to weigh the benefits of health insights against their personal comfort levels with this type of technology.” Ya think? 
     
  • Recent research in the news: 
     
  • Funding news of note:
     
  • From AIin.Healthcare’s news partners:
     

 

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