AI Changed the Fundraising Landscape, Here’s the New Playbook to Nail Your Pitch

1. Why a New Fundraising Playbook is Needed

AI has changed how companies are built & the way they scale. As founders are adapting to this new reality, the way venture capitalists evaluate startups also changed.

Most successful fundraising rounds start with a standout deck, but the old fundraising frameworks & templates you can find online, pre Gen AI era, simply don’t cut it anymore.

Using generic SaaS fundraising templates is like trying to fit a square peg into a round hole— confusing for investors and generally misjudging AI businesses. We think AI-native startups need a pitch deck that reflects their rapid evolution and unique strengths.

-> Here is our Series A Deck Template for AI Applications as a Google Slides presentation <-

Below, you will find additional context and key learnings we drew as VCs in the past months to evaluate the new generation of AI companies scaling. As well as a slide-by-slide written ‘voiceover’ to help you, founders, create a winning pitch deck. 

We have made it in Google Slides so that you can easily make a copy and personalize it, or use it as a mental framework for a better Figma design. We hope it will help you successfully pitch your startup to us at Headline, or to whomever you choose as your partners.

Not Only for Series A Founders

While many have ridden the first AI wave in 2023 and 2024 to raise early-stage funding with limited metrics, the Series A stage demands more.

Investors now expect founders to demonstrate a deep understanding of their tech stack, data strategy, and competitive edge. Yet most founders are still using outdated templates, misaligned with the realities of this post-GPT era.

Our primary goal is to create a pitch deck for AI Apps founders who are raising Series A rounds in the coming months. This template is specifically tailored for them. However, it can just as easily serve as a foundation for founders at earlier stages (pre-seed/seed) or more mature stages (Series B+), as well as for businesses with different models (infrastructure, marketplaces, fintech, etc.).

This template seeks to be a state-of-the-art guide designed to help founders articulate their vision with clarity, depth, and precision. Whether you’re building in AI or not, it equips you to stand out in today’s crowded and competitive fundraising landscape. This isn’t just an update—it’s a playbook for the future.

2. How Do VCs Think About the AI Fundraising Landscape?

The Generative AI revolution created a new wave of startups—AI-native companies where AI capabilities are the core of their business. As first investors in Mistral AI (foundational model layer), we now see a whole new generation of companies on the application layer, the AI Apps, operating with different rules from traditional SaaS or Fintechs. These rules are defined by dynamic infrastructure, data-centric growth drivers, and evolving retention models.

Across all the geographies and stages Headline invests in, we have witnessed a new paradigm emerge from AI-native startups. The foundational models haven’t just created new opportunities and challenges; they have changed how markets and investors think about scale, defensibility, and innovation.

While many incumbents—including the GAFAM titans (Google [Alphabet], Apple, Facebook [Meta], Amazon, and Microsoft)—scramble to consolidate their dominance, a new generation of challengers like OpenAI, Anthropic, xAI and Mistral AI aim to rewrite the playbook with bold strategies and record-setting funding rounds.

This moment has also tested the conviction of VCs and created a clear divide between those willing to back transformative visions and those waiting for the dust to settle. We decided to embrace the frontier instead of the familiar.

Evaluating these AI application companies requires a complete perspective shift; traditional frameworks fall short when assessing their potential. Success in this domain demands a nuanced understanding of their unique dynamics and value-creation paths.

Below, we outline some of the main changes we observe in VC before providing a written voiceover for the new template we have put together to address them.

Investors Are Rethinking What Metrics Mean

First, a hard truth: the retention profile of a company is now the most critical indicator of long-term viability. In hyper-competitive markets, where adoption and integration present significant hurdles, retention reveals far more about sustainability than top-line growth alone. 

Low Net Dollar Retention (NDR) is the number one reason VCs pass on AI apps rounds these days, questioning the sustainability of these businesses in potentially crowded markets with questionable moats…

Gross margins also require a more nuanced lens. New cost drivers—such as computing expenses—now appear in COGS (Cost of Goods Sold), compressing margins but often serving as a source of competitive advantage rather than the red flag they often were in pre-AI eras. These costs, when managed strategically with technological optimization, can underpin scalability and defensibility.

The top line in these AI-native startups is often more volatile, with exponential growth becoming a standard for best-in-class Series A companies (“0 to 1m of ARR in 6-12 months, 5-10x’ing the year after). However, assessing the quality of the revenues & the growth is a challenge: growth is now rigorously assessed in tandem with retention metrics to ensure it reflects durable value creation rather than fleeting momentum.

Competitive Advantages No Longer Follow The Same Hierarchy

Competitive advantages are also evolving. The true value of AI applications lies not just in scale, but in access to differentiated data—proprietary, exclusive, or in some cases synthetic—coupled with the technology to process and leverage it effectively. This virtuous cycle of data utilization drives product evolution, enhances the user experience, and can ultimately maximize ROI. In this new era, data is finally king.

Moreover, deep integration into clients’ existing workflows, coupled with seamless onboarding and support, is key to increasing switching costs and driving stickiness and long-term adoption. Business model innovation & pricing creativity offer another critical avenue for differentiation. The paradigm shift in AI isn’t about transforming processes, but outcomes. As a result, outcome-based business models are poised to replace usage-based or per-seat approaches, setting a new standard for value creation.

Last but not least, distribution will be pivotal, shaping both the pace of growth and retention, especially for AI applications where differentiation will hinge less on technology and more on strategic distribution. In an oversaturated market marked by strong competition and a lot of noise, reimagining your distribution approach can be the key to establishing a category leader position. This not only accelerates growth but also reinforces brand equity and triggers powerful network effects.

Big the First-Mover Advantages, Bigger Equity Stories

First-mover advantages are more important than ever, with investors eager to see entrepreneurs stake their claim in markets that are now suddenly open for disruption. With a tidal wave of capital eager to fuel this race, VCs are adopting the role of market makers like never before. Would domain-specific AI for law firms buzzy Harvey have become Harvey without raising $200M in two years with Sequoia, Conviction etc.?  What about 11x, maker of AI agents for sales, RevOps, and go-to-market? Capital is never just fuel; it’s a statement of intent.

For AI app founders, the equity story, fundraising milestones, and the caliber of your investors are more critical than ever. They don’t just shape your trajectory—they determine your ability to define new categories and establish leadership.

Considering the speed at which new-generation AI companies are built these days, the Narrative matters more than ever, and so does your Fundraising deck - the one main tool you can use to support your Narrative. 

A Crowded Market

The rise of AI Applications has drastically increased competition in the fundraising landscape. These startups grow at an unprecedented pace, leveraging accessible AI tools, open-source models, and rapid prototyping capabilities to achieve remarkable velocity and explosive metrics. While this presents immense opportunities, it also creates a noisy and crowded market. Investors are inundated with pitches, making it harder than ever for founders to stand out.

In such a competitive environment, a clear, concise, and compelling fundraising deck isn’t just a tool—it’s a necessity. It’s the first filter through which investors evaluate opportunities. Without a deck that cuts through the noise, even exceptional startups risk being misunderstood and overlooked.

What Makes a Winning Deck Today

A winning deck isn’t about overwhelming investors with buzzwords or technical jargon. It’s about clarity of thought, precision, and focus. After reading your deck once, an investor should:

• Understand your product at a high level
• Grasp the market opportunity and why you’re uniquely positioned to win.
• Identify and drive conclusions out of the key metrics showcased
• Get the long-term Narrative and assess the sustainability of your business 
  

But the deck goes beyond this. A great fundraising deck serves not only as an entry ticket for a first meeting but also as a reference tool throughout the investment process. The clearer and more detailed your deck, the easier it is for investors to build conviction and align with your vision.

Stand Out by Being Transparent and Complete

AI-native startups, by their nature, are complex. But complexity doesn’t mean founders should drown investors in buzzwords or hide behind vagueness. Instead, founders should clearly explain the AI concepts underpinning their business, demystifying technical details while showing how these elements drive differentiation.

By providing a comprehensive yet accessible narrative, founders can ensure their vision is understood, their metrics are appreciated, and their potential is clear. In today’s crowded AI landscape, clarity isn’t just an advantage—it’s essential.

3. Slide-by-Slide Voice-Over: the Headline Series A Pitch Deck Template for AI Apps

Overview

When crafting this slide, aim for maximum clarity and factual precision. This is the investor's first impression—these elements will anchor your company in their mind. Use a visual that reflects your industry while evoking modernity. Prominently display your logo. The stronger the logo placement, the more memorable your company will be.

Clearly indicate the funding stage you’re raising. This provides immediate context about your development stage and helps the investor quickly assess fit with their thesis. Investors value clarity and efficiency—time is a premium resource.

Crafting the company statement requires precision. It should be compelling yet free of hyperbole. Avoid grandiose, overly dramatic claims that can come across as unconvincing. Instead, focus on creating a crisp, memorable statement that encapsulates your business in a way investors can easily repeat to colleagues or partners.

Above all, steer clear of clichés like, “We’re the Uber of…” Uber is Uber. Even if your business aims to disrupt a category in a similar way, frame it differently. Develop your unique narrative—one that sets you apart and authentically communicates your vision.

Executive Summary

Now that you’ve captured the reader’s attention, it’s time to fully engage them. The goal is to make the investor want to open your deck in full screen, intrigued by the potential of discovering a gem.

This executive summary must strike a balance: simple yet highly informative. Focus on four key pillars:

• Value Proposition: In 1–2 sentences, explain what your business offers. Be professional and less salesy than your statement, and mention the business model, target audience, and market.
• Competitive Edge: Highlight 1–2 reasons why your startup will dominate its category. What sets you apart? Whether it’s your tech, team, distribution wedge, data, or something else, make it crystal clear. Your company’s Narrative hinges on this.
• Flagship Clients: Showcase key customers to establish credibility and legitimacy. These clients validate your value and help attract others. Mention secondary or tertiary ICPs as well, as they indicate growth potential.
• Key Metrics: Share your Annual Recurring Revenue (ARR), growth rate, and other critical Key Performance Indicators (KPIs) that demonstrate strength—Annual Contract Values (ACVs), payback time, or anything else that reinforces your position. Investors need to see your momentum.

Team

This slide should demonstrate why your team is uniquely qualified to win in this market with this value proposition. For example, if you’re building a copilot for IP lawyers and professionals, you’ll need team members with deep expertise in intellectual property, ideally from established industry players. Similarly, if your focus is payroll for large enterprises, you should prioritize hiring talent with advanced skills and a thorough understanding of this highly technical domain. These niche profiles are rare but invaluable, giving you a significant edge over competitors who lack access to such specialized expertise.

In AI and tech, top talent is scarce and fiercely competed for by major players like leading large language model (LLM) companies or extremely well-funded AI-native startups. Highlight how you’ve recruited tier-1 talent in your field. This is a proof point of your ability to attract and retain exceptional people, proving your project’s appeal and signaling that your team can outpace competitors.

Specifically for AI, emphasize research papers, patents, reputation, and network strength—these are potential differentiators. A strong tech team must be complemented by operational and go-to-market (GTM) talents. The right balance between technical excellence and execution capability is critical.

Pain point

The pain point you’re addressing is the cornerstone of finding your product-market fit (PMF). A great product that only marginally improves the status quo will struggle to gain traction due to natural resistance to change and organizational inertia. The bigger the pain point and the less effective existing solutions are at solving it, the more compelling your value proposition becomes.

Strengthen your argument with market data, macro trends, or other evidence that proves the pain point is significant and widespread. Avoid anecdotal examples—this isn’t about solving Martine’s internal tool struggles; it’s about addressing a systemic, undeniable issue.

Solution

The solution slide is key in your pitch deck, yet we often see it inadequately presented.

Keep it straightforward and remember that you're addressing an investor, not a technician, customer, or friend. The investor needs to clearly understand the type of product—be it SaaS, an intelligent agent, co-pilot, AI-enabled service, etc.—as well as the end user and the type of business in which they operate. It's important to delineate whether your startup is focused on a specific vertical market or operates horizontally, catering to a variety of industries.

Clarify what the product does and what problem it solves for the end user. What functionalities does it enable? Additionally, explain how it integrates with the existing array of tools. 

Finally, quantify the impact of your product. This could include enhancements in productivity or quality, revenue generation, or even the potential to replace entire departments. Investors often show more interest in direct revenue opportunities rather than productivity metrics. Provide concrete data or estimates to illustrate the quality and economic impact of your product, helping investors grasp the tangible benefits it delivers.

Product Demo

A demo can make or break your pitch. Nothing beats a sharp, concise video to showcase your product. Make sure it’s tight and compelling—that after watching, any confusion about your product clears up completely. If an investor already grasps your product, your demo should impress them with its slick interface and seamless user experience. Keep it short, make it punchy.

Product Features & Roadmap 

In this slide, you need to demonstrate both the breadth and depth of your product's AI capabilities. Clearly articulate the upcoming AI initiatives and the timeline for their rollout. Timing is crucial—it's a competitive race, so you must deliver quickly and execute flawlessly. A well-defined plan, outlined distinctly by the Founder, ensures rapid and effective execution. Focus on the AI features you plan to develop, as they are central to your competitive edge, but do not overlook the importance of user experience and integration.

At Headline, we aim to partner with companies that exhibit exceptional product velocity and a vision that transcends their initial product wedge. What is your long-term vision for your product? Will you focus on becoming the best-in-class point solution for your ICP, or will you adopt a compound business software strategy, like Rippling, by building multiple products in parallel to become the Operating System for an industry—a category that may not have existed just years ago?

Why Now

The "why now" is critical as it creates urgency. It should convince the investor that we’re at a pivotal market moment where new possibilities are emerging, and now is the time to sprint into the opportunity. Importantly, "why now" isn’t about why we’re fundraising now; it’s about why this product must be built now.

The reasons can be multifaceted. For an AI founder, it often ties to breakthroughs enabled by large language models (LLMs) or unprecedented access to public, private, or synthetic data. But it can also stem from qualitative factors like shifts in innovation perception, regulatory changes, or cultural trends.

The goal is to show that your company is addressing a hot, high-stakes problem—one at the center of the most exciting and fast-moving category. Make it clear that this wave is transformative for the tech landscape in your target industry and that this is the moment to place a bet before the opportunity is gone.

We typically love it when there is a technological breakthrough (AI) that allows the automated execution of partial or complete tasks in an industry in which the shortage of talents (manually executing these tasks) is increasing. 

Use Cases & ROI

Customer satisfaction decides whether a product is good or not. Provide detailed information on specific use cases for your product and highlight those that best demonstrate its effectiveness with flagship clients. This not only shows your ability to secure key customers but also appeals to investors. Include a quote from a customer that is not overly promotional but factual, illustrating how they benefit from using your product. If you have a visual representation of your product's interface or its usage that adds value, include it; otherwise, omit unnecessary visuals. Additionally, provide quantitative ROI data from the use of your product, noting that ROI can vary depending on the use case (more revenues generated, time saved, replacement of an employee etc.).

AI products often offer quantifiable time savings over more manual processes. E.g., "5 hours of monthly admin work vs 50." You can use this slide to explain how your product impacts or redefines the workflows, or makes new processes possible.

Market Sizing

The market sizing slide often gets a bad reputation: it can be dismissed by investors due to inflated or unrealistic projections in many decks. Since investors will recalculate the market from raw data anyway, provide clear, grounded numbers and align with them on the final figures. Not understanding your market sizing well is a real red flag. 

First, focus on the market you’re addressing today (SOM), clearly explain your methodology, and avoid overselling. This calculation should be based on your current ICP and pricing—the one you’re actually charging clients at the time of creating your deck, not the pricing you aspire to achieve in the future. Having an initial market size of hundreds of million dollars isn’t prohibitive for a VC as it can represent a market related to the initial wedge only —a unique entry point into much larger markets that can be unlocked through long-term strategies.

Next, outline the calculation for your medium-term and longer term market sizes. These larger future markets can typically be accessed through:

• New product offerings
• New ICPs
• Expansion into new geographies
• Adjustments to pricing strategies or unlocking new monetization streams with scale

Above all, ground your assumptions in raw, realistic data. Avoid presenting generic, overly polished figures from external reports without detailed backing—investors can see through that quickly.

That said, VCs understand that with the AI revolution, market dynamics are shifting significantly in both structure and scale. While today’s market boundaries are fluid, conducting realistic, data-driven calculations remains an essential exercise for any entrepreneur.

Traction Overview

This is where your numbers need to shine—investors want a clear, compelling view of your performance and potential. A concise, data-driven approach to your metrics will instill confidence and set you apart.

Start with the fundamentals: Annual Recurring Revenue (ARR), growth (Month-over-Month [MoM] and Year-over-Year [YoY]), and unit economics like Average Contract Value (ACV), Customer Acquisition Cost (CAC), and CAC payback time. These establish the strength of your go-to-market (GTM) motion and your understanding of your Ideal Customer Profile (ICP).

For AI-native startups, gross margin and Net Dollar Retention (NDR) are especially critical.

• AI app gross margins might be lower than traditional SaaS due to higher compute, inference, or data costs. Be transparent and show how you’re optimizing these costs over time.
• Net Dollar Retention (NDR) reveals revenue growth or decline within your customer base, factoring in upgrades, downgrades, churn, and renewals. With the explosion of AI tools, adoption often lags after trials due to integration issues or low engagement. Investors scrutinize NDR as a key indicator of retention and long-term growth, so demonstrate your focus on improving it.

Last but definitely not least for AI Apps, include usage metrics to highlight product adoption. These help investors understand how you pilot your business and ultimately assess upsell potential and churn risk, showing how sticky and scalable your product is. As retention is often a concern for AI Apps, double clicking even more on product usage is a must (more below in the Product Usage section).

GTM

A strong Go-To-Market (GTM) strategy is essential for AI startups to differentiate and scale effectively. Start by defining your Ideal Customer Profile (ICP) and clearly distinguishing between sponsors (decision-makers) and end users. For example, enterprise AI solutions often target executives for sponsorship while enabling technical teams with intuitive tools. Tailor your motion accordingly, whether through outbound sales, product-led growth, or paid marketing, emphasizing ROI for sponsors and seamless usability for end users.

Strategic partnerships can also be critical. Collaborations with system integrators, cloud providers, or consulting firms as indirect distributors provide access to established markets and enhance credibility. Partnering with major AI players or large incumbents strengthens your positioning while aligning with key industry trends.

Community engagement drives organic growth. Focus on building ecosystems through technical workshops, research papers, or active participation in AI communities like Discord or GitHub. These initiatives not only build trust but position your startup as a thought leader in the space.

Finally, you can include market breakdowns by industry or geography if this level of granularity benefits your pitch.

ARR & Growth

Including a simple graph of your ARR, with optional projections for the current year, is essential for clarity and impact. This visual snapshot helps investors quickly grasp your revenue trajectory and growth potential. Accompany the graph with a concise text to contextualize any significant fluctuations, whether related to ICP shifts, GTM adjustments, product enhancements, regulatory impacts, seasonal trends, or major client acquisitions.

For example, if ARR growth accelerated due to a successful product launch or expansion into a high-growth vertical, highlight this as evidence of scalability. Conversely, if growth decelerated due to regulatory changes or seasonal challenges, transparently explain the context and outline how these challenges are being addressed. This approach not only demonstrates accountability but also showcases your understanding of market dynamics and operational agility.

Monthly Cohorts

Revenue cohort analysis is essential for understanding and optimizing Net Dollar Retention (NDR), a key metric for AI startups. By tracking cohorts, you gain insight into customer stickiness, upsell potential, and the health of your growth model beyond new acquisition.

Positive trends in cohorts reveal strong adoption and upsell success, while declines highlight churn risks or ICP mismatches. Highlight how technical adoption or new features drive growth in specific cohorts and explain any anomalies caused by external factors, such as market shifts or seasonality.

For AI startups, cohort analysis could also highlight AI-specific metrics, such as usage-based revenue (e.g., API calls or model inference volume). These insights reflect how customers engage with the product over time, helping to identify trends in adoption and scalability. Additionally, technical adoption cycles often result in ramped-up usage post-integration, leading to higher revenue potential. Showing how new features or integrations drive growth within certain cohorts can underscore both product-market fit and the scalability of your offering. These AI-focused insights enhance the understanding of customer behavior and demonstrate the product’s ability to generate sustainable growth.

Net New ARR

Net New ARR is a key indicator of the efficiency and repeatability (and acceleration!) of your GTM strategy, as it directly reflects the revenue generated from acquiring new customers. From a technical standpoint, this metric provides insights into both the speed of market penetration and the effectiveness of sales motions in driving customer acquisition.

In AI startups, where product complexity and integration are often barriers to rapid adoption, tracking Net New ARR helps evaluate how well your GTM strategy is overcoming these challenges.

Net Revenue Per Month

To effectively assess your Net Revenue, break it down into upsell, new customers, churn, and contraction:

• Upsell: Measures expansion within existing accounts, typically driven by the adoption of higher-tier services or additional features. In AI, this shows how deeply customers are integrating your product, revealing stickiness and cross-sell opportunities.
• Net New Revenue: Represents revenue from new customers, key for evaluating sales velocity and market penetration. In AI, new customer acquisition can be influenced by new model releases or enhanced features that attract fresh users.
• Churn: Customer attrition highlights product fit and retention. In AI, churn often results from poor onboarding, integration issues or curious users willing to try and leave... A high churn rate alongside growing new revenue signals potential lack of Product Market Fit.
• Contraction: Measures revenue decline from existing customers, such as downgrades.

This breakdown provides actionable insights, helping optimize GTM strategies and pinpoint where to focus retention or expansion efforts.

Product Usage

Usage metrics are critical for understanding retention and churn, as they reflect how well your product engages users. Key indicators, such as the number of active users or queries processed, can provide valuable insights into product adoption, usability, and stickiness. For AI startups, this could mean tracking interactions with your AI model, feature usage, or the frequency of API calls. High usage typically signals strong product-market fit, while a decline may indicate usability issues, lack of engagement, or friction in the customer experience.

AI Architecture 

Including a tech stack slide in your AI pitch deck is essential to showcase the sophistication and adaptability of your infrastructure. Highlight the use of cutting-edge AI concepts such as Large Language Models (LLMs), Self-Learning Models (SLMs), Retrieval-Augmented Generation (RAG), and Reinforcement Learning from Human Feedback (RLHF), which differentiate your product by enhancing language understanding, data retrieval, and iterative learning.

Emphasize the scalability and flexibility of your infrastructure, ensuring it can handle growing data demands and seamlessly integrate with new models and technologies. Stress that your stack is modular and future-proof, avoiding reliance on a single vendor or LLM, and can adapt to emerging AI advancements.

Finally, showcase your commitment to continuous improvement through data-driven training and real-time inference, ensuring that your models evolve and stay competitive over time. This reassures investors that your technology is robust, scalable, and adaptable to the fast-evolving AI landscape.

Business Model

AI startups often need to rethink traditional SaaS business models. Rather than relying solely on fixed pricing for tools, usage-based or outcome-based pricing models are more effective in capturing the real value generated by AI technology. These models align pricing with the actual results or usage, ensuring that customers pay for the value they receive.

The gross margin structure in AI is typically influenced by costs such as data preparation, inference, and model training. It’s crucial to demonstrate how you plan to optimize these costs over time, ensuring a sustainable path to long-term profitability.

Additionally, stickiness and upsell potential are critical for growth. Strategies such as land-and-expand, offering new features, or integrating with other tools can help maintain customer engagement and drive revenue from existing accounts. Focusing on these strategies helps build a loyal customer base while increasing lifetime value.

Competitive Landscape

One of the most critical slides in your pitch deck is the competitive landscape. This slide maps out your position within the market, providing investors with a clear view of who your competitors are and where you stand in comparison.

Personalize the matrix based on the factors that matter most to your business—whether it's technology, distribution channels, data advantages, or other aspects directly tied to your vision.

In AI, the competitive challenge is particularly complex: competition comes from both agile startups, established enterprises or simply human workforce (people-intensive agencies for intensive). This dual pressure can make your moat appear more vulnerable. AI models evolve rapidly, and shifts in technology can quickly render a product obsolete unless you're continuously innovating. This reality underscores the need for long-term sustainability, and highlights why protecting your competitive position isn’t just about keeping up with tech advancements.

You must differentiate through additional strategic levers such as exclusive data access, AI-specific integrations, or strong customer relationships that larger players struggle to replicate. These factors, when combined with a robust technology stack, help mitigate risks associated with rapidly changing models and ensure your market position remains secure.

Competition Deepdive

Investors need to understand your competitive landscape and why your startup stands out. In AI, competition doesn’t just come from other startups—it’s also from established incumbents. Given the rapid advancements in AI models, it's crucial to demonstrate that your competitive edge extends beyond just technology.

Begin by identifying your direct competitors and incumbents whose market share you're targeting. Don't overlook adjacent players who may represent indirect competition. Strengthen your analysis by including details about funding rounds and notable investors for these competitors. Highlight that while a single fundraising round in a category may seem isolated, multiple rounds in the same space—especially with tier-1 investors—signal an emerging trend. If applicable, reference international role models and explain how your approach will enable you to outperform them.

Beyond technology companies, whether legacy incumbents or new-generation startups, AI tools face another competitor: the human workforce.

AI applications excel particularly at automating manual, repetitive tasks that follow clear, fixed rules and require minimal creative or cognitive input. While this aspect of AI can evoke fear and hostility, it’s crucial not to overlook that competition may come from people-intensive industries focused on processed, repetitive tasks (a translation agency with 30 translators might reduce its workforce to 3 by adopting AI tools).

For AI startups, replacing human labor in such contexts can serve as a compelling wedge. This approach not only strengthens the product offering but also unlocks the potential for a compound effect enabling the creation of a comprehensive product suite. In doing so, they transform industries traditionally reliant on verticalized human efforts for manual, repetitive tasks.

Lastly, clearly articulate why your approach is superior, and outline your long-term vision to become the category leader in the next 10 years. This slide not only helps investors understand the market dynamics but also showcases your strategy for dominating the space in the future.

AI Specifics Competition Advantage

The moat is one of the most crucial but often underestimated elements in any pitch deck. In a market where barriers to entry are constantly evolving, traditional competitive advantages remain important, but AI introduces new, powerful opportunities to build sustainable moats.

These moats stem from three core pillars: proprietary data, technology, and strategic integrations. First, your data—whether public, private, or synthetic—becomes a key differentiator as it enhances your models and drives product improvements. Over time, the quality and exclusivity of this data provide a significant competitive advantage, allowing you to continually refine your AI capabilities.

Second, the agility of your tech stack plays a critical role. A flexible, scalable infrastructure that can adapt quickly to changing market conditions and new opportunities strengthens your position. In AI, this means that the faster you can iterate and evolve your product, the harder it becomes for competitors to catch up.

Finally, integrations with established platforms (through APIs or partnerships) help lock users into your ecosystem, increasing customer stickiness. The deeper your solution integrates into their workflows, the more embedded it becomes, making it harder for competitors to displace. These strategic alliances with key players—whether through partnerships or technical integrations—create a defensible position and enhance your product’s long-term value.

This slide should clearly communicate how your startup is actively building and evolving these barriers, positioning it for market leadership. Demonstrating a strong, evolving moat not only reassures investors of your company's ability to defend against competitors but also highlights the sustainable, long-term value you're creating.

High-Level Business Plan & Key Milestones

Highlight the targets you have for the following 24 months. The main topics to cover are internationalization, ARR targets and product expansion. Also, you can mention gross margin evolution if this metric needs to be streamlined over time considering the cost structure of your business, or any other relevant metric evolution.

Set ambitious yet realistic goals. Ground your objectives in solid, credible assumptions while maintaining a resolutely ambitious outlook.

When pitching international expansion, outline your plan chronologically, highlighting market maturity, local regulations (e.g., GDPR), and compliance challenges. Show how your product will adapt to local demands and detail your operational strategy, including office setup, hiring, and scaling talent. This proves your plan is structured, compliant, and growth-ready.

Fundraising

To conclude, outline your post-funding plan clearly, showing how the capital will be utilized to achieve your next major milestones. You can break down how the funds will be allocated—whether it’s for scaling infrastructure with more compute resources, hiring top-tier talent, expanding marketing efforts, or opening new offices in strategic locations. Demonstrate that the funding requirement is not inflated but directly aligned with your growth ambitions. Investors need to understand how this capital will enable the company to scale effectively, secure leadership in your category, build moat and optimize margins. Be transparent about your resource needs and the specific objectives the funds will help you achieve, ensuring that the amount requested is justified by your company’s strategic growth plan.

Epilogue

Leave a good but sharp impression. Just the company logo + the name and picture of the co-founder in charge of the fundraising and how to contact them are enough.

Lastly, it's essential to prepare a more comprehensive deck that addresses specific elements related to your own market and category. For instance, you could include slides on the value chain and key stakeholders or the legislation and regulatory requirements that shape your product's environment.

Additionally, a slide highlighting the key risks your company faces in this market is a smart move. Investors, especially those advocating for your funding internally, will need to understand the risk profile of your business.  Remember, risks are not inherently prohibitive; they are a part of venture investing, and VCs would rather make bold bets on potential game-changers than miss out on extraordinary opportunities. Presenting risks upfront with a thoughtful analysis will set the stage for productive and challenging discussions. A good practice is to provide an initial framework for these risks, which will also serve as a starting point for meaningful conversations.

After building the deck, be prepared to share a well-organized data room (that might be another piece of content we will think about putting together if we have demand from founders).

Are you building an exciting AI app? Scaling and raising a Seed or Series A round?  If so, we want to meet you!

Reach out to jon@headline.com and astrid@headline.com, or to any member of our team. 

We believe we are in the very early days of a complete shift in how software & platforms are created and scaled. And that it will only accelerate from here. If you’re building innovative solutions in the AI app space, we’d love to hear from you.