Piyumi Kapugeekiyana

Charith Gunasekara

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The State of GenAI Adoption A cross-industry exploration with a spotlight on startups

GenAI x industry hero

The State of GenAI Adoption: A cross-industry exploration with a spotlight on startups

<div>
 <ul>
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 Enterprise GenAI adoption is led by digitally-inclined industry verticals.
 
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 Emerging industries: GenAI adoption is highest in healthcare and pharmaceuticals industry, followed by financial services. Key functions include core business operations, research and product development, and customer experience.
 
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 Further value addition may be driven by industry-agnostic GenAI (e.g. Marketing Automation)
 
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 </ul>
 
 
</div>

<div>
 
 The state of GenAI in the enterprise
 
 
 
 <ul>
 <li>
 
 Strong potential for value addition tempered by long timelines for implementation: 
 Enterprise GenAI adoption can unlock an annual equivalent of 
 <a href="https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#business-value">
 USD 2.6 trillion&ndash;4.4 trillion
 </a>
 in value across the global economy, but the timeline for realizing these benefits is drawn out, with 
 <a href="https://kpmg.com/us/en/media/news/kpmg-generative-ai-2023.html">
 ~60% of US executives
 </a>
 and 
 <a href="https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-state-of-gen-ai-report.pdf">
 ~68% of global business leaders
 </a>
 indicating their organizations were still at least 1&ndash;3 years away from implementing their first GenAI solution and witnessing the benefits of transformation.&nbsp;
 
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 <li>
 
 Adoption led by digitally inclined, knowledge-based industry verticals: 
 Global GenAI adoption is led by technology, media, and telecom (TMT), followed by the financial services sector. Middle-of-the-pack adopters include consumer goods/retail, aerospace and defense, pharma and healthcare, and energy and utilities.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 Highest value to be derived from four business functions: 
 An estimated 
 <a href="https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#key-insights">
 ~75% of the value
 </a>
 to be derived from GenAI use cases is expected to stem from four areas: 1) customer operations, 2) marketing and sales, 3) software engineering, and 4) R&amp;D.&nbsp;
 
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 </ul>
 
 
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 <li>
 
 Industry alliances can accelerate enterprise adoption: 
 Developer-led collaborations (between GenAI developers and tech partners) and consultancy-driven partnerships (between consulting firms and GenAI developers) can play an important role in enhancing the general accessibility of GenAI solutions as well as in supporting and scaling enterprise adoption, respectively.&nbsp;
 
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 </ul>
 
 
 
 GenAI adoption in emerging industries
 
 
 
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 <li>
 
 Highest incidence of GenAI activity in healthcare and pharmaceuticals: 
 Emerging industries engaged in providing and improving healthcare services, such as 
 <a href="https://sp-edge.com/industry/29">
 Telehealth
 </a>
 , 
 <a href="https://sp-edge.com/industry/79">
 Hospital Interoperability
 </a>
 , and 
 <a href="https://sp-edge.com/industry/106">
 Hospital Management
 </a>
 , showed the strongest propensity for adoption, with a range of GenAI-focused activities focused on either developing the technology in-house or leveraging third-party GenAI.
 &nbsp;
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 High activity also observed in financial services: 
 In line with broad global patterns around knowledge-based industries, emerging financial services industries like 
 <a href="https://sp-edge.com/industry/36">
 Neo Insurance
 </a>
 , 
 <a href="https://sp-edge.com/industry/53">
 FinTech Infrastructure
 </a>
 , and to a lesser extent, 
 <a href="https://sp-edge.com/industry/59">
 Neobanks
 </a>
 , also showed a high incidence of GenAI activity.
 
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 </ul>
 
 &nbsp;
 
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 <li>
 
 Strongest potential for value creation through three business functions: 
 Core business operations, research and product development, and customer experience witnessed the highest levels of GenAI activity across the emerging industries. By extension, companies looking to generate value through GenAI adoption need to prioritize relevant, industry-specific use cases across these functions. In healthcare, for example, enabling GenAI for core business operations may involve use cases like patient care administration or supporting diagnostics and treatment. Comparatively, in financial services, it may include underwriting or fraud detection.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 Further value addition may be driven by industry-agnostic GenAI: 
 Our research suggests that companies in emerging industries have also leveraged GenAI to develop solutions for general business functions. This includes industries like 
 <a href="https://sp-edge.com/industry/62">
 Marketing Automation
 </a>
 (for customer analysis and content creation), 
 <a href="https://sp-edge.com/industry/51">
 Next-gen Cybersecurity
 </a>
 (to develop security assistants, automate coding, and bridge data silos), and 
 <a href="https://sp-edge.com/industry/157">
 Supply Chain Tech
 </a>
 (for item description generation, supplier recommendations, and negotiation summaries). The industry-agnostic nature of these solutions has likely supported the current high enterprise adoption in marketing and sales as well as software engineering. It also indicates emerging industries could accelerate GenAI enablement beyond the three fundamental business functions.
 
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 </ul>
 
 
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 AI-driven drug discovery is significantly reducing R&amp;D time and costs, with startups nearing commercialization.
 
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 Health and pharma companies are using novel technologies such as gene editing, cell therapeutics, and nanopore sequencing to provide tailored healthcare and treatments. 
 
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 </ul>
 
 
</div>

Healthcare & Pharma top picks: AI and personalization fuel new era of health innovation

Artificial intelligence is identifying and testing new therapies faster than ever.

AI Drug Discovery

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 <ul>
 <li>
 
 Generative biology is one of the newest tools in the AI drug discovery toolbox; it focuses on designing entirely new therapeutics from scratch using GenAI
 
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 Demand is driven by the promise of higher clinical success rates and the ability to treat &lsquo;undruggable&rsquo; diseases&nbsp;
 
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 Players include AI-first drug discovery startups, and Big Pharma and Big Tech incumbents entering the space through partnerships
 
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 </ul>
 
 
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<div>
 <ul>
 <li>
 
 Generative biology is one of the newest tools in the AI drug discovery toolbox, and refers to the design of novel biomolecules with desired structures and properties using existing protein data. It combines generative AI, ML, innovations in biology, and automation to create these new protein therapeutics.
 
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 Demand is driven by the potential for generative biology to be used to design therapeutics for &quot;undruggable&quot; diseases. In addition, its use in the drug discovery process can increase the accuracy of the newly designed therapeutics thereby increasing the success of clinical trials.
 
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 Players in this space include several AI-first drug discovery companies that have adopted generative biology, as well as Big Pharma and Big Tech incumbents that have entered the space through partnerships with startups.
 
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 To generate new protein designs, AI/ML models must be trained on the many naturally occurring protein sequences to recognize complex patterns within them. The more data they are fed, the better their output.
 
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 </ul>
 
 
</div>

EDGE Insights

The State of GenAI Adoption: A cross-industry exploration with a spotlight on startups

Healthcare & Pharma top picks: AI and personalization fuel new era of health innovation

The LEGO of life: Building new organisms with generative biology

The State of GenAI Adoption: A cross-industry exploration with a spotlight on startups

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