Piyumi Kapugeekiyana

Charith Gunasekara

application/vnd.openxmlformats-officedocument.wordprocessingml.document

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>
 <li>
 
 Enterprise GenAI adoption is led by digitally-inclined industry verticals.
 
 </li>
 <li>
 
 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.
 
 </li>
 <li>
 
 Further value addition may be driven by industry-agnostic GenAI (e.g. Marketing Automation)
 
 </li>
 </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;
 
 </li>
 <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;
 
 </li>
 </ul>
 
 
 <ul>
 <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;
 
 </li>
 </ul>
 
 
 
 GenAI adoption in emerging industries
 
 
 
 <ul>
 <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.
 
 </li>
 </ul>
 
 &nbsp;
 
 <ul>
 <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.
 
 </li>
 </ul>
 
 
</div>

<div>
 <ul>
 <li>
 
 Startups developing foundation models show unsurprising domination as these large models continue to evolve and prove value across numerrous use cases.
 
 </li>
 <li>
 
 GenAI hardware players fare well as demand for powerful and efficient hardware skyrockets, while end-user GenAI applications are starting to shift away from general-purpose chatbots to specialized &quot;co-pilot&quot; solutions.
 
 </li>
 </ul>
 
 
</div>

<div>
 <ul>
 <li>
 
 Foundation models show unsurprising domination,
 as these versatile large models continue to evolve and have demonstrated proven value across numerous use cases.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 In 2023, companies developing foundation models collectively raised over $21 billion in funding&mdash;the highest of any industry in SPEEDA Edge. However, nearly 85% of this funding was concentrated toward big players such as OpenAI and Anthropic.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 GenAI hardware players fare well as demand for powerful and efficient hardware skyrockets. 
 Startups developing hardware solutions to tackle the compute challenges associated with GenAI have thrived in this year&rsquo;s top picks. Hardware developers tailored specifically for GenAI workloads such as 
 <a href="https://sp-edge.com/companies/1453946">
 d-Matrix
 </a>
 and 
 <a href="https://sp-edge.com/companies/596587">
 Lightmatter
 </a>
 accounted for over 40% of all funding in the GenAI infrastructure space.
 
 </li>
 </ul>
 
 
 <ul>
 <li>
 
 End-user GenAI applications also made their mark,
 as startups offering purpose-built applications for specific industry use cases fared better, indicating a shift away from general-purpose chatbots toward more specialized &quot;co-pilot&quot; solutions tailored to individual sectors.
 
 </li>
 </ul>
 
 
</div>

AI/ML top picks: The GenAI arms race accelerates

Exploring the limitless possibilities of AI

Generative AI Applications

<div>
 <ul>
 <li>
 
 Ten generative AI companies raised a total of USD 264 million in disclosed funding during Q1 2023
 
 </li>
 <li>
 
 Several regulatory challenges also emerged during early 2023, driving AI legislation.
 
 </li>
 </ul>
 
 
 
 
</div>

EDGE Insights

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

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

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