Artificial intelligence (AI) is transforming businesses in unprecedented ways. As companies across sectors adopt intelligent technologies to drive efficiency, innovation, and growth, AI can further shape valuations and investment dynamics.
The influence of AI is particularly conspicuous in the IPO landscape. This blog post analyses how AI could sway upcoming IPOs (Initial Public Offerings), from facilitating better price discovery to enabling superior post-IPO stock performance.
The Surge in AI IPOs
Industry experts expect a spate of tech IPOs focused on AI solutions. From AI chips to ML platforms, from autonomous vehicle technology to predictive analytics, AI startups can be expected to attract massive funding and investor attention.
Many of these well-funded AI startups are primed to go public soon. AI-led enterprise software companies like Fractal, IdeaForge, and Table Space are expected to be among the high-profile AI IPOs on the horizon.
In addition to pure-play AI firms, a broad swath of AI-powered companies across e-commerce, digital health, fintech, logistics, and other sectors is set to hit public markets. As AI capabilities become embedded in diverse operational and business verticals, they are altering traditional value creation models.
Investors have rewarded AI-led innovation and digital transformation strategies with premium valuations during the recently completed tech IPOs.
How AI is Transforming the IPO Process
From marketing the offering to pricing the issue and even post-IPO stock performance, let us consider the various touchpoints where AI could influence upcoming IPOs:
1. More Personalised IPO Marketing
Marketing an IPO to the right mix of institutional and retail investors is pivotal for the offering’s success. AI is enhancing the precision of IPO marketing in multiple ways:
Firstly, machine learning algorithms can analyse past IPO investor data to create focus lists of prospective investors likely to be interested in the upcoming issue based on their mandates and prior investment patterns. Such AI-enabled targeting can help streamline IPO roadshows and one-on-one meetings for the management by connecting them with the most relevant investors from the outset.
Secondly, as interactions between bankers, investors, and prospects increase across digital channels, AI can help personalize IPO marketing. Leveraging data from multiple sources, AI solutions can create detailed profiles of investors to help companies gain insights into their areas of interest and curate customized IPO content. Such hyper-personalization at scale can improve engagement and issue participation.
2. More Accurate IPO Pricing
Arriving at the right IPO price is a delicate balancing act. The company wants to raise adequate capital while leaving something for investors to generate aftermarket excitement. AI is making the pricing sweet spot more straightforward to find.
IPO pricing depends considerably on gauging investor demand for the issue. Earlier, estimating demand involved the bookrunner’s intuition and raw feedback from roadshow meetings. AI augments this subjective demand analysis with hard data.
AI algorithms can analyse multiple parameters, such as investors’ prior bidding history, market sentiment on comparable stocks, overall market dynamics surrounding the issue, and expected participation of retail investors, to build demand forecasts.
This data-backed pricing power gives bankers more confidence in guiding the issuer toward an optimal IPO price, neither leaving too much value on the table nor overpricing the issue.
Besides pricing, AI enables innovative moves like adopting a range of prices in IPO filings. This dynamic pricing approach aligns better with data-driven demand indications before the offering. Companies are increasingly adopting AI-powered solutions to price their IPOs dynamically.
3. Superior Aftermarket Performance
The utility of AI does not end once a company goes public. Instead, AI enables superior operational and stock market performance post-IPO.
Due to their lack of experience as listed entities, IPO firms often struggle with managing reporting compliance, disclosures, financial planning and analysis, and investor relations. Migrating from private to public financial workflows can be complex.
Several AI-powered software solutions now simplify these post-IPO transition challenges spanning across compliance, finance, operations, and Incident Response (IR) functions:
- AI algorithms can help automate compliance with changing regulatory requirements, reducing compliance costs and risks.
- ML algorithms can help FP&A (Financial Planning & Analysis) teams model IPO impacts, support accurate quarterly forecasts, and provide real-time performance monitoring.
- AI chatbots and virtual assistants can handle vast inbound queries from new public investors and shareholders post-IPO.
- Predictive algorithms enable proactive IR by identifying future risks, such as litigation, short-seller attacks, negative media coverage, etc., before they can tank the stock.
Such AI-enabled automation of cumbersome IPO workstreams allows the management to stay strategic. Listed companies leveraging AI exhibit superior efficiency in servicing public market stakeholders. This institutionalisation and professionalisation of post-IPO capabilities ultimately help catalyse better stock performance.
Evaluating AI-Powered IPOs
As AI permeates the IPO landscape, investors need to incorporate relevant AI dimensions while evaluating upcoming IPO deals:
- Assess if the IPO firm has strategic clarity on how AI aligns with its value creation model and complements existing strengths.
- Review if AI capabilities are embedded internally within the business or if the firm relies on external partnerships and vendors. Internal leverage indicates robust AI competencies.
- Estimate the Total Addressable Market (TAM) expansion potential as AI augments the company’s offerings to target new outcomes and use cases.
- Benchmark AI-related KPIs like tech stack costs, ML model accuracy, explainability, transparency, etc., versus immediate competitors.
- Validate whether the AI strategy cuts across siloed functions or operates in isolated pockets within the company. Cross-functional AI adoption should demonstrate organizational readiness.
Framework for Evaluating AI-Powered IPOs
Thus, when assessing AI-led IPOs, investors must thoroughly evaluate the issuing firm’s standalone AI capabilities and organizational AI readiness across management vision, strategy, implementation, and adoption.
The framework below covers some key areas of inquiry while evaluating IPOs from AI-centric businesses:
Assessment Avenue | Details |
AI Technical Capabilities | Proprietary datasets and data strategy
ML model robustness and fairness Explainable and ethical AI practices Technology architecture and stack AI Business Impact |
Revenue exposure to AI offerings | AI’s expansion potential beyond core business
Competitor benchmarking on AI adoption AI Commercial Viability |
Unit economics of AI products | Contribution of AI to platform stickiness
AI’s role in enhancing efficiencies AI Organisational Readiness |
Executive leadership commitment to AI | Levels of AI talent and technical skills
AI awareness and adoption across the workforce AI governance and change management plans |
The Bottom Line
IPO markets are poised to see heightened AI influence going forward, both from emerging AI startups and incumbent enterprises pursuing AI-led transformation. As intelligent technologies permeate upcoming IPOs, investors must incorporate new data points centered on AI technical capabilities, business impact, commercial viability, and organisational readiness while evaluating these companies.
AI’s growing presence makes the IPO domain more dynamic. But it also introduces new risks related to data transparency, model robustness, and algorithmic accountability that investors should be wary of. Overall, IPO issuers that leverage AI ethically, responsibly, and comprehensively across their organisations inspire more confidence in creating sustainable public market value.
Frequently Asked Questions
Q1: How is artificial intelligence shaping the IPO landscape?
A1: AI is revolutionizing IPOs by enhancing market analysis, streamlining financial data processing, and improving decision-making for both issuers and investors. AI tools provide sharper insights into a company’s valuation and growth potential that facilitate pricing. AI also introduces data-driven objectivity to balance out human subjectivity for evaluating an IPO’s success.
Q2: Can I determine share prices using AI tools?
A2: Top stock brokers in India offer AI-based stock price recommendations. For example, one can access share prices like SBI Life share price by visiting their platforms.
Q3: Can AI predict the success of an IPO?
A3: While AI cannot guarantee foolproof predictions regarding an upcoming IPO’s aftermarket performance, algorithms can analyse past IPO data, overall market sentiment, competitive factors, and investor behavior to predict the likelihood of oversubscription and strong listing gains. So AI provides evidence-based probability assessments even if absolute success forecasting remains challenging.
Q4: What role does AI play in IPO pricing?
A4: Arriving at the optimal IPO price is tricky but critical. AI algorithms can help financial advisors and issuers determine the ideal price band by assessing prevailing market dynamics, financial ratios, investor demand signals, and prices of comparable stocks. Rather than gut feeling, data models can inject greater objectivity into price setting.
Q5: How does AI influence investor behavior during IPOs?
A5: AI-based tools are making IPO investments more appealing and accessible to a wider pool of investors. Personalised recommendations, predictive analytics, automated risk profiling, and real-time market insights provided by AI-driven platforms can attract more interest from retail investors for IPOs.
Q6: Are there risks associated with using AI in the IPO process?
A6: The risks with AI-powered IPO solutions include over-reliance on algorithms, data biases creeping into models, lack of transparency, and vulnerability to cyberattacks. The issuing firm needs robust governance to ensure the accuracy and suitability of AI systems used for IPOs. The human oversight element remains critical.
Q7: Could AI impact the sectors dominating upcoming IPOs?
A7: AI could steer more IPO activity from sectors at the forefront of digital transformation, such as technology, healthcare, fintech, e-commerce, and logistics. AI-based innovations in these industries can make their business models more appealing to public investors. AI prowess can influence which sectors can see increased IPO volumes going forward.
HussaiN is a full-time professional blogger from India. He is passionate about content writing, tech enthusiasts, and computer technologies. Apart from content writing on the internet, he likes reading various tech magazines and several other blogs on the internet. Email ID: arrowtricks.pvt@gmail.com
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