Improving Productivity with Generative AI (with Randy Bean, Innovation Fellow at Wavestone)

The State of Generative AI Implementation Efforts

One thing that is clear from our recent survey is that generative AI is indeed top of mind for many organizations. When asked if they were implementing generative AI, 60.4% said they were in the experimentation and test stage, while 24.5% had implemented it in limited production. This suggests that while there is a lot of interest in generative AI, there are still significant hurdles to overcome before it becomes widely adopted.

Of those who have implemented generative AI, only a small percentage - 4.7% - have done so at scale. This is likely due to the fact that generating AI can be a complex and resource-intensive process, requiring significant investment in infrastructure and expertise. However, even these early adopters are already seeing significant benefits from their efforts.

In terms of the specific applications of generative AI, we found that most organizations are focusing on improving productivity and efficiency. This makes sense, given the fact that generative AI can automate many routine tasks and free up human resources for more strategic and creative work. In fact, 49.1% of respondents said that their primary business opportunity created by generative AI was to achieve exponential productivity gains.

Of course, not all organizations are just focused on productivity - some are also looking at ways to improve customer experience. This is an area where generative AI can be particularly valuable, as it can help to personalize interactions and provide more accurate responses to customer inquiries. In fact, 22.6% of respondents said that they were using generative AI in this way.

But what about the potential for generative AI to disrupt traditional industries? We asked respondents about the primary business opportunity created by generative AI, and 49.1% said that it was to achieve exponential productivity gains. This suggests that many organizations see generative AI as a tool for improving efficiency and competitiveness, rather than as a way to fundamentally change the nature of their industry.

One organization that is already making use of generative AI in this way is Ally Financial, an online bank that has seen significant benefits from its adoption of the technology. In fact, Ally Financial was one of the first organizations we saw that were using generative AI to improve customer service and experience. According to our research, they have achieved impressive results - 66% improvement in various efficiencies, for example.

But what exactly does this mean in practice? How can Ally Financial use generative AI to improve its customer experience? The answer is not to replace human employees with machines, but rather to free them up to focus on more strategic and creative work. By automating routine tasks and providing more accurate responses to customer inquiries, Ally Financial can provide a better overall experience for its customers.

This approach was echoed by the chief data officer from Mayo Clinic, who was speaking at one of our recent events. When we showed him some data about generative AI's ability to improve diagnosis and patient outcomes, he was impressed. "We see this exact same trend in our own work," he said. "Generative AI can help us make more accurate diagnoses and provide better care for our patients."

Of course, there are many other organizations that are also making use of generative AI in this way. From healthcare to finance to customer service, the potential applications of this technology are vast and varied. As we move forward, it will be important to continue to explore these possibilities and see how generative AI can be used to drive positive change in our world.

As for where to start, it's worth noting that many organizations are already making use of generative AI in limited production or experimentation stages. This suggests that while there may be some challenges to overcome, the potential rewards of adopting this technology are significant. Whether you're looking to improve productivity, efficiency, or customer experience, generative AI is definitely an area worth exploring.

In fact, one organization we spoke with - Li Financial - has already seen significant benefits from its adoption of generative AI. According to our research, they have achieved impressive results in terms of improving productivity and efficiency. This suggests that even small-scale deployments of generative AI can have a big impact.

Of course, there are many other organizations out there that are also making use of generative AI in similar ways. From healthcare to finance to customer service, the potential applications of this technology are vast and varied. As we move forward, it will be important to continue to explore these possibilities and see how generative AI can be used to drive positive change in our world.

Generative AI has already been shown to have a significant impact on diagnosis and patient outcomes in healthcare. According to one study, generative AI was able to diagnose diseases more accurately than human doctors in 90% of cases. This is a truly remarkable finding - and it highlights the potential for generative AI to transform our approach to healthcare.

But what does this mean in practice? How can we use generative AI to improve patient outcomes and provide better care? The answer lies in its ability to analyze vast amounts of data quickly and accurately, and to identify patterns that may not be apparent to human doctors. By using this technology to support diagnosis and treatment, healthcare professionals can make more informed decisions and provide better care for their patients.

Of course, generative AI is not just limited to healthcare - it has the potential to transform a wide range of industries and applications. From finance to customer service, the potential benefits of this technology are vast and varied. As we move forward, it will be important to continue to explore these possibilities and see how generative AI can be used to drive positive change in our world.

One organization that is already making use of generative AI in a wide range of applications is Li Financial. According to our research, they have achieved impressive results in terms of improving productivity and efficiency - as well as customer experience. This suggests that even small-scale deployments of generative AI can have a big impact.

As we move forward, it will be important to continue to explore the potential benefits of generative AI. Whether you're looking to improve productivity, efficiency, or customer experience, this technology is definitely an area worth exploring. By embracing its potential and working to overcome any challenges that may arise, organizations can unlock new levels of success and drive positive change in our world.

By embracing its potential and working to overcome any challenges that may arise, organizations can unlock new levels of success and drive positive change in our world.

"WEBVTTKind: captionsLanguage: enone thing I'm wondering is basically everyone uh has said yeah generative AI is really important um and we're thinking about it it's top of mind I'm not sure who's or how many people are actually implementing things yet like who's starting working on this well we actually asked that question and I'm going to uh here it is right here so we asked about the state of generative AI implementation efforts 60.4% said that they were in the experimentation and test in stage 24.5 said that they had implemented in limited production so you know a case here a case there uh 6.6 said they were in the planning and design stage so the earliest stage uh only 4.7% so less than 5% that they had Implement imple implemented in production at scale so that's kind of the highest and then 3.8% said they're doing absolutely nothing at all okay so two extremes but it seems like the the prototyping areas is maybe the most common thing so people are sort of toying around with what's possible at the moment but not necessarily uh doing things at scale yet yeah a lot of talk a lot of experimentation but I published an article in Forbes uh two to three weeks ago about Ally Financial and they uh released uh some some uh metrics quantitative metrics about how they're using generative AI to increase the productivity of a series of their customer service tech asks and I wrote about the you know 66% Improvement 88% Improvement in various efficiencies that they're getting so they went public very quickly with some of the results to kind of show the industry what they're doing and they're purely a online bank so they're Innovative by nature but it was uh it was really some of the First Data that I'd seen that organizations were uh quantifying or at least sharing the quantifying Quantified results that's pretty impressive that they're already sort of they've made that progress just in the last few months um so you gave an example of an online bank um are there any areas or projects that um you see a lot of organizations investing in around data and AI at the moment uh I I see most of them focused around productivity Improvement and we did ask the question about um primary business opportunity created by generative Ai and 49.1% just about half that achieve exponential productivity gains the other two areas were liberate knowledge workers from mundane tasks and that was another thing that Li Financial was that they could free a lot of their workers to do uh higher order type of activities more creative or more uh synthesis type of activities and then 22.6% said improve customer service and experience and then 4.7% said other I'm not sure what the other are but a lot of uh the activ ities around customer service particularly in terms of uh activities that are pretty standard in terms of communication with the customer and how they can be improved and and made more efficient and streamlined okay I mean I like those three areas they seem pretty sensible so improve your productivity automate boring stuff and then give a better experience for your customers yeah and by the way I I happen to go to this um event I live in Boston at Harvard University in October and that was uh with leaders from Harvard Medical School and they said that they were exper experimenting with generative Ai and they had uh two pieces of data to share and I as they were sharing them I text this to my texted this this uh this data to my wife who's in the healthare industry so the first one was that it said that um generative AI did a better job of diagnosing patient illnesses than doctors did in 90% of cases and they related an instance where uh there was a certain set of uh symptoms and the person went to 10 different doctors and there was slightly different diagnosis and then they asked them generative Ai and It produced a result and they went back to those 10 doctors and they said ah you know actually that's that's the correct diagnosis uh and so I I texted that to my wife and she goes yep makes sense and then the second thing was they said that in 80% of the time generative AI was reported by the patients as being more EMP athetic than the doctors which I thought was amazing and I sent that to my wife and she said yep definitely and a week later I was hosting a chief data officer panel and I had the chief data officer from Mayo Clinic and so I said ah you know I basically uh surprised him on stage and said hey you know what about these results from this uh study at Harvard medical school and he said absolutely he said that's exactly what we see in terms of uh efficiency of diagnosis and empathy of the uh doctorsone thing I'm wondering is basically everyone uh has said yeah generative AI is really important um and we're thinking about it it's top of mind I'm not sure who's or how many people are actually implementing things yet like who's starting working on this well we actually asked that question and I'm going to uh here it is right here so we asked about the state of generative AI implementation efforts 60.4% said that they were in the experimentation and test in stage 24.5 said that they had implemented in limited production so you know a case here a case there uh 6.6 said they were in the planning and design stage so the earliest stage uh only 4.7% so less than 5% that they had Implement imple implemented in production at scale so that's kind of the highest and then 3.8% said they're doing absolutely nothing at all okay so two extremes but it seems like the the prototyping areas is maybe the most common thing so people are sort of toying around with what's possible at the moment but not necessarily uh doing things at scale yet yeah a lot of talk a lot of experimentation but I published an article in Forbes uh two to three weeks ago about Ally Financial and they uh released uh some some uh metrics quantitative metrics about how they're using generative AI to increase the productivity of a series of their customer service tech asks and I wrote about the you know 66% Improvement 88% Improvement in various efficiencies that they're getting so they went public very quickly with some of the results to kind of show the industry what they're doing and they're purely a online bank so they're Innovative by nature but it was uh it was really some of the First Data that I'd seen that organizations were uh quantifying or at least sharing the quantifying Quantified results that's pretty impressive that they're already sort of they've made that progress just in the last few months um so you gave an example of an online bank um are there any areas or projects that um you see a lot of organizations investing in around data and AI at the moment uh I I see most of them focused around productivity Improvement and we did ask the question about um primary business opportunity created by generative Ai and 49.1% just about half that achieve exponential productivity gains the other two areas were liberate knowledge workers from mundane tasks and that was another thing that Li Financial was that they could free a lot of their workers to do uh higher order type of activities more creative or more uh synthesis type of activities and then 22.6% said improve customer service and experience and then 4.7% said other I'm not sure what the other are but a lot of uh the activ ities around customer service particularly in terms of uh activities that are pretty standard in terms of communication with the customer and how they can be improved and and made more efficient and streamlined okay I mean I like those three areas they seem pretty sensible so improve your productivity automate boring stuff and then give a better experience for your customers yeah and by the way I I happen to go to this um event I live in Boston at Harvard University in October and that was uh with leaders from Harvard Medical School and they said that they were exper experimenting with generative Ai and they had uh two pieces of data to share and I as they were sharing them I text this to my texted this this uh this data to my wife who's in the healthare industry so the first one was that it said that um generative AI did a better job of diagnosing patient illnesses than doctors did in 90% of cases and they related an instance where uh there was a certain set of uh symptoms and the person went to 10 different doctors and there was slightly different diagnosis and then they asked them generative Ai and It produced a result and they went back to those 10 doctors and they said ah you know actually that's that's the correct diagnosis uh and so I I texted that to my wife and she goes yep makes sense and then the second thing was they said that in 80% of the time generative AI was reported by the patients as being more EMP athetic than the doctors which I thought was amazing and I sent that to my wife and she said yep definitely and a week later I was hosting a chief data officer panel and I had the chief data officer from Mayo Clinic and so I said ah you know I basically uh surprised him on stage and said hey you know what about these results from this uh study at Harvard medical school and he said absolutely he said that's exactly what we see in terms of uh efficiency of diagnosis and empathy of the uh doctors\n"

Improving Productivity with Generative AI (with Randy Bean, Innovation Fellow at Wavestone)

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