Summary of Morgan Stanley TMT Conference: The Early Stage of the Big Opportunity in AI

On March 8th, Morgan Stanley pointed out in the TMT conference report that the potential of generative AI market is enormous, but it is still in its early stages.

Analysts like Keith Weiss emphasized five key points of generative AI in the report, highlighting that the Retrieval-Augmented Generation (RAG) architecture is becoming the main architecture for generative AI applications.

Morgan Stanley stated that although the commercialization process of generative AI takes time, software vendors have already achieved significant productivity gains through internal AI tool applications.

AI's big opportunity is still in its early stages, with innovation speeding up

Morgan Stanley believes that the market opportunity for generative AI is huge. Software vendors are enthusiastic about expanding the capabilities of generative AI and emerging market opportunities.

However, they also caution investors to be patient as the commercialization process of generative AI products will take time. For example, OpenAI's CEO Sam Altman stated that the development of generative AI is still in its early stages, and we are still "exploring as we go."

Morgan Stanley observed that the pace of innovation in generative AI tools is accelerating.

Sam Altman of OpenAI mentioned that GPT-5 will achieve significant leaps in functionality, similar to the transition from OpenAI to GPT-4. Microsoft also expects that the features and innovations of M365 Copilot will be improved almost daily, but the peak of innovation has not yet arrived.

Rise of the Retrieval-Augmented Generation (RAG) architecture

Morgan Stanley pointed out that the RAG architecture is becoming the main architecture for generative AI applications. This architecture aims to ensure the accuracy and timeliness of solutions driven by Large Language Models (LLMs). Although the RAG architecture is still in the early stages of the innovation cycle, it has become an early standard.

However, Morgan Stanley also noted that despite the clarity of the architecture, developing generative AI solutions remains challenging.

Issues such as data quality, data security, accuracy, and dispelling illusions are difficult to resolve. In addition, workflows have not yet been integrated into core language models or generative AI, which may drive demand to shift more quickly towards application vendors with scale and technical resources.

According to Morgan Stanley, many companies are currently using generative AI tools, significantly improving the productivity of developers, marketing, customer service, and sales.

For example, Atlassian mentioned using Atlassian Intelligence internally, where virtual agents have handled about 50% of call volumes. This indicates that software vendors have achieved better profit margin improvements internally. President Anu Bharadwaj of the application software company Atlassian:

With over 300,000 customers, Atlassian has a huge market opportunity, especially driven by cloud services, which helps unlock these opportunities further.

Atlassian Intelligence is resonating with over 20,000 customers, with its generative AI capabilities being implemented across the platform, rapidly expanding innovative use cases.

Atlassian's cloud transformation is progressing as planned, and the management is satisfied with the current progress, even exceeding internal targets in some cases.

CEO George Kurtz of software and services company CrowdStrike Holdings:

CrowdStrike's single-agent architecture makes it a true platform company, facilitating deployment and module switching.

Charlotte AI from CrowdStrike integrates collective knowledge from the past decade, helping organizations automate SOCs and optimize productivity.

With an ARR exceeding 150 million, the SIEM field is facing disruption, and CrowdStrike has a competitive advantage as about 85% of threat data originates from endpoints.

CEO David McJannet and CFO Navam Welihinda of the open-source cloud service foundation platform HashiCorp:

Driving monetization through differentiation: HashiCorp motivates customers to pay by expanding the functional gap between commercial and free products.

Improvements in cloud consumption and demand environment: Management expects that improvements in the cloud consumption and overall demand environment by hyperscale cloud service providers will eventually benefit HashiCorp's model.

Market changes: HashiCorp has implemented market changes, including streamlining sales actions and shifting towards an upper market.

Cloud-first strategy: Management leans towards a cloud-first strategy and is committed to attracting customers on cloud platforms first, enabling them to realize value faster.

President Eugene Levin and CFO Brian Mulroy of the digital marketing management platform Semrush Holdings:

Enterprise market growth: Semrush is investing in product and market strategies to better serve enterprise customers, providing significant opportunities for the company.

Profit margin expansion: Despite higher customer acquisition costs for higher-end market clients, Semrush is expected to achieve profit margin expansion through internal AI automation and data-driven cross-selling strategies.

Impact of AI on SEO and product portfolios: The development of GenAI technology requires marketers to learn how to navigate new experiences and interfaces, and Semrush is expected to help customers better understand chat-based search. Chief Financial Officer Joe Del Preto and President Ryan Barretto of social media management software service provider Sprout Social:

Market positioning and financial goals: Sprout Social has enhanced confidence in achieving a 120% Net Revenue Retention (NRR) target by shifting towards the upper market.

Pricing strategy: Sprout Social's pricing strategy is expected to deliver a 7% growth by 2024, as price increases are fully reflected in the model, and the company has overcome the impact of low-end customer churn.

Opportunities with Tagger: Sprout Social sees opportunities to expand the average deal size by cross-selling Tagger through its acquisition. Significant progress has been made. With the continuous advancement of technology, generative AI will undoubtedly play a crucial role in the future software industry.