Digital Assistants are here to help. And we think they’re here to stay.  They’re already among us, of course. Most of us think nothing of asking them to play some mood music, avoid traffic on our way to a friend’s wedding, or point us in the direction of the best meal in town.  As digital assistant technology gets better, and as AI’s full impact on it is realized, how much more help might we need?  We think the answer is a lot and that digital assistants will play an increasingly central role in our lives across a range of uses. In this report we’ll look at a few of these potential use cases and how they can help make our lives more efficient, as well as provide proprietary insight into the potential size of the market.

AI Time: AI Assistants Are Coming For You

Administration is a part of healthcare that’s often underappreciated by outsiders. It’s also currently very inefficient and therefore ripe for disruption by AI. Here’s why it’s important: Excessive cost: Very roughly one-quarter of all spending on healthcare in the US is on administrative tasks, but automation could save perhaps 25-30% of this. Burden on clinicians: Burnout is an increasing problem in many health systems globally, including in the US, and more than 90% of clinicians say excessive admin is contributing to burnout. Industry fragmentation: Friction in the flow of information means the healthcare system is currently split into distinct entities, e.g., the providers, payers, and government, with little integration among them, and misaligned incentives. “It’s easy to think that sorting out health admin isn’t that sexy,” according to Dr. Avi Mehra, a co-founder of Doctorpreneurs and CSO in IBM’s health tech team. “But there will probably be more improvement in healthcare provision, for less effort by applying AI to health administration, relative to the clinical side.” Healthcare Industry -- Fragmentation and Consolidation © 2023 Citigroup Inc. No redistribution without Citigroup’s written permission. Source: Deloitte Consulting, Citi Global Insights AI is already starting to help automate a great deal, and the authors believe that the advent of really good understanding of ordinary language will accelerate this. “AI presents a large opportunity to help reduce bottlenecks and automate several areas of health admin,” says Elliot Jenks, a managing director at Citi’s investment bank, responsible for health services. “That means you could make a lot of processes much more efficient and lower cost.” The authors also believe that, in the future, faster information flows among the various parts of the healthcare system will mean they will become more integrated, focusing more and more on the benefits for the consumer. It is hard to overstate just how burdensome administration is for clinicians. There is unprecedented stress among clinicians following Covid, and poor, disconnected IT is a major factor: “Clinicians are spending too much time working on admin tasks like pre-authorization scheduling and answering prescription questions that could be automated," says Morgann Carlon, a Health AI leader at Deloitte. According to one survey of US clinicians: 92% of clinicians agree that admin is a major contributor to healthcare worker burnout. 36% of clinicians spend more than half their time on administration. The full report goes on to discuss several other areas, including ambient administration in which a smart AI assistant could listen to the conversation between patient and doctor with the AI behind it and help extract relevant information. It also looks at how AI could improve care for patients, as it can effectively triage, organize, and deliver care to those most in need. For more information on this subject, and if you are a Velocity subscriber, please see the full report, published on 25 April 2023, here: https://www.citivelocity.com/ And here are the previous reports in this series: Smart Thinking on AI in Healthcare: Part 1 – Overview Smart Thinking on AI in Healthcare: Part 2 – Medical Devices Citi Global Insights (CGI) is Citi’s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click here.

&nbsp;
Administration is a part of healthcare that&rsquo;s often underappreciated by outsiders. It&rsquo;s also currently very inefficient and therefore ripe for disruption by AI. Here&rsquo;s why it&rsquo;s important:
<ul>
<li>Excessive cost: Very roughly one-quarter of all spending on healthcare in the US is on administrative tasks, but automation could save perhaps 25-30% of this.</li>
</ul>
<ul>
<li>Burden on clinicians: Burnout is an increasing problem in many health systems globally, including in the US, and more than 90% of clinicians say excessive admin is contributing to burnout.</li>
</ul>
<ul>
<li>Industry fragmentation: Friction in the flow of information means the healthcare system is currently split into distinct entities, e.g., the providers, payers, and government, with little integration among them, and misaligned incentives.&nbsp;</li>
</ul>
&ldquo;It&rsquo;s easy to think that sorting out health admin isn&rsquo;t that sexy,&rdquo; according to Dr. Avi Mehra, a co-founder of Doctorpreneurs and CSO in IBM&rsquo;s health tech team. &ldquo;But there will probably be more improvement in healthcare provision, for less effort by applying AI to health administration, relative to the clinical side.&rdquo;
Healthcare Industry -- Fragmentation and Consolidation
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64ef5e7f860feb324c9fed50.png" width="711" height="413" />
&copy; 2023 Citigroup Inc. No redistribution without Citigroup&rsquo;s written permission.
Source: Deloitte Consulting, Citi Global Insights
AI is already starting to help automate a great deal, and the authors believe that the advent of really good understanding of ordinary language will accelerate this.
&ldquo;AI presents a large opportunity to help reduce bottlenecks and automate several areas of health admin,&rdquo; says Elliot Jenks, a managing director at Citi&rsquo;s investment bank, responsible for health services. &ldquo;That means you could make a lot of processes much more efficient and lower cost.&rdquo;&nbsp;
The authors also believe that, in the future, faster information flows among the various parts of the healthcare system will mean they will become more integrated, focusing more and more on the benefits for the consumer.
It is hard to overstate just how burdensome administration is for clinicians. There is unprecedented stress among clinicians following Covid, and poor, disconnected IT is a major factor:
&ldquo;Clinicians are spending too much time working on admin tasks like pre-authorization scheduling and answering prescription questions that could be automated," says Morgann Carlon, a Health AI leader at Deloitte.
According to one survey of US clinicians:
<ul>
<li>92% of clinicians agree that admin is a major contributor to healthcare worker burnout.</li>
</ul>
<ul>
<li>36% of clinicians spend more than half their time on administration.</li>
</ul>
The full report goes on to discuss several other areas, including ambient administration in which a smart AI assistant could listen to the conversation between patient and doctor with the AI behind it and help extract relevant information. It also looks at how AI could improve care for patients, as it can effectively triage, organize, and deliver care to those most in need.&nbsp;
For more information on this subject, and if you are a Velocity subscriber, please see the full report, published on 25 April 2023, here: <a href="https://www.citivelocity.com/" target="_blank" rel="noopener" data-link-source="tiny">https://www.citivelocity.com/</a>
And here are the previous reports in this series: 
 <a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQzMjE5" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 1 &ndash; Overview</a> 
<a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQ1MjEz" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 2 &ndash; Medical Devices</a> 
Citi Global Insights (CGI) is Citi&rsquo;s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click <a href="https://ir.citi.com/6A3IURUaezPxFLppsgdBkqidjLaLn558JwHISYaDZcTfE9XMRB1isDDDVorqrxpR%2fTnEi4RUCl8%3d" target="_blank" rel="noopener" data-link-source="tiny">here</a>.

A recent report from Adam Spielman of Citi Global Insights looks at the possibilities for AI to impact health administration, potentially cutting costs and helping ease the huge burden on clinicians. 

AI in Healthcare: Health Administration 

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Generative AI has burst onto the scene following the launch of ChatGPT in 2022. As a concept, artificial intelligence (AI) is not new, and Generative AI represents the latest inflection point in the evolution of AI. However, what is distinctive about Generative AI is the tremendous potential it holds to transform work across industries and boost overall productivity. Taking a more holistic view, Generative AI might not only bring the power of AI itself to the masses but in fact accelerate the wider democratization of innovation. We believe it is a game changer. Although it feels like Generative AI has come out of nowhere, the rise of AI starting in the 1950s and through its significant growth over the past decade. This growth has brought with it a host of potential opportunities and challenges. The first wave of potential opportunities for Generative AI is centered on the technology value stack. Historically, the Silicon layer has been the de facto foundation of almost all technological shifts in the technology value stack, and Generative AI is expected to drive significant growth for compute (i.e., processing power), networking, and memory chips. However, we see opportunities in each layer. In the Infrastructure & Platforms layer, we see the hyperscalers/cloud providers racing today to build the underlying infrastructure that enables Generative AI applications and services, but over time we expect to see higher or more differentiation. When it comes to Models and Machine Learning Operations (MLOps), the open-source community is likely to be a key driver of innovation. Moving further up the stack, we believe nearly all software companies will be impacted in some form by Generative AI, and company-specific execution will be critical. Lastly, we believe Generative AI represents a step forward from ongoing AI/automation initiatives at the Services layer. Opportunities are not just limited to the technology value stack —they are also spilling into sectors outside of technology. To capture the full picture, we extended our analysis to look at the impact of Generative AI across six supersectors. We do this through a two-stage framework to assess risk/reward and apply that broadly across companies and sectors. Our analysis finds the Financials & FinTech supersector to be the most likely to be impacted overall, followed by the Consumer sector. At the other end of the spectrum, Natural Resources & ClimateTech at this stage look the least likely ones to be impacted. Key challenges include those centered around bias, inequality, authenticity, infringements as well as the more debated one underpinned by existential concerns. The emergence of Generative AI has unsurprisingly seen AI as a broader topic become a firm focus for policy makers around the world. However, the regulatory path taken so far has varied. Given the stakes involved, we believe policy and governance evolution will play a defining role. What does the future look like for Generative AI? We investigate the global trends and growth is from the perspective of investment in technological innovation. We do this by analyzing the number of AI-related patent applications over time and across countries. Research papers are also telling, with the total cumulative AI research output increasing 1,300% between 2003 and 2021. Given the importance of AI as a foundational technology, the race is on between countries for scientific and technological dominance.

Generative AI has burst onto the scene following the launch of ChatGPT in 2022. As a concept, artificial intelligence (AI) is not new, and Generative AI represents the latest inflection point in the evolution of AI. However, what is distinctive about Generative AI is the tremendous potential it holds to transform work across industries and boost overall productivity. Taking a more holistic view, Generative AI might not only bring the power of AI itself to the masses but in fact accelerate the wider democratization of innovation. We believe it is a game changer.
Although it feels like Generative AI has come out of nowhere, the rise of AI starting in the 1950s and through its significant growth over the past decade. This growth has brought with it a host of potential opportunities and challenges. The first wave of potential opportunities for Generative AI is centered on the technology value stack. Historically, the Silicon layer has been the de facto foundation of almost all technological shifts in the technology value stack, and Generative AI is expected to drive significant growth for compute (i.e., processing power), networking, and memory chips.
However, we see opportunities in each layer. In the Infrastructure &amp; Platforms layer, we see the hyperscalers/cloud providers racing today to build the underlying infrastructure that enables Generative AI applications and services, but over time we expect to see higher or more differentiation. When it comes to Models and Machine Learning Operations (MLOps), the open-source community is likely to be a key driver of innovation. Moving further up the stack, we believe nearly all software companies will be impacted in some form by Generative AI, and company-specific execution will be critical. Lastly, we believe Generative AI represents a step forward from ongoing AI/automation initiatives at the Services layer.
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64f7dc62b7581721266e09ae.png" alt="Tech" />
Opportunities are not just limited to the technology value stack &mdash;they are also spilling into sectors outside of technology. To capture the full picture, we extended our analysis to look at the impact of Generative AI across six supersectors. We do this through a two-stage framework to assess risk/reward and apply that broadly across companies and sectors. Our analysis finds the Financials &amp; FinTech supersector to be the most likely to be impacted overall, followed by the Consumer sector. At the other end of the spectrum, Natural Resources &amp; ClimateTech at this stage look the least likely ones to be impacted.
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64f7dc83c1acef4c8ae226e1.png" alt="Supersectors.JPG/" />
Key challenges include those centered around bias, inequality, authenticity, infringements as well as the more debated one underpinned by existential concerns. The emergence of Generative AI has unsurprisingly seen AI as a broader topic become a firm focus for policy makers around the world. However, the regulatory path taken so far has varied. Given the stakes involved, we believe policy and governance evolution will play a defining role.
What does the future look like for Generative AI? We investigate the global trends and growth is from the perspective of investment in technological innovation. We do this by analyzing the number of AI-related patent applications over time and across countries. Research papers are also telling, with the total cumulative AI research output increasing 1,300% between 2003 and 2021. Given the importance of AI as a foundational technology, the race is on between countries for scientific and technological dominance.

What does the future look like for Generative AI? One way to investigate the global trends and growth is from the perspective of investment in technological innovation. We do this by analyzing the number of AI-related patent applications over time and across countries. Research papers are also telling, with the total cumulative AI research output increasing 1,300% between 2003 and 2021. Given the importance of AI as a foundational technology, the race is on between countries for scientific and technological dominance.

The AI Arms Race

Generative AI represents the latest inflection point in the evolution of artificial intelligence (AI). Although AI is not new, what is distinctive about Generative AI is the tremendous potential it holds to transform work across industries and boost overall productivity. We look at the opportunities for AI not only in the technology sector but across six supersectors. Given the race to dominate in the AI space, we also analyzing research papers and patents by country.

Unleashing AI

Devika Kornbacher, Partner and Co-Head of the Global Tech Group and Dessislava Savova, Partner and Head of the Continental Europe Tech Group at Clifford Chance joined us to compare the EU-US regulatory approaches with respect to AI in financial services.  Common themes in existing rules and standards include accountability, transparency and explainability.  The proposed EU AI Act is the first comprehensive Regulation of AI which is expected to apply to all industries with very few exceptions and have extraterritorial reach.   We anticipate a final version of the AI Act will be agreed by the beginning of 2024.  In contrast, US regulators and policymakers are mainly relying on existing rules and regulation by enforcement, supplemented by frameworks on the horizon from several agencies.  Globally we have seen different jurisdictions take different approaches with no globally agreed framework yet in place. We anticipate an EU-US code of conduct in the future.