this graph explains why you can’t make money with AI

Summiz Holo

Technology adoption life cycle, chasm, and distinct market segment characteristics

• The technology adoption life cycle outlines the stages of how different segments of the population adopt new technologies, including innovators, early adopters, early majority, late majority, and laggards.
• The 'chasm' refers to the gap between early adopters and the early majority, which many software companies struggle to bridge.
• Each segment of the population has distinct characteristics and needs that influence how they should be marketed to.
• Innovators are interested in the potential of technology and often have resources to invest, while early adopters are visionaries who experiment with real-world applications.
• The early majority is more pragmatic and requires proof and evidence before adopting new technologies, making them more risk-averse compared to earlier segments.

Targeting Early Adopters for AI Solutions Amid Skeptical Majority

• The market for AI technology adoption is primarily focused on business owners, not general consumers.
• The current phase of AI adoption is transitioning from early adopters to the early majority, which is more pragmatic and requires proof before adopting new technologies.
• Early adopters are visionaries and risk-takers who are excited about trying new technology, while the early majority is more skeptical and evidence-based.
• Selling AI solutions to the early majority is challenging without prior proof or evidence of effectiveness.
• New AI agency owners should target early adopters, as they represent a small segment of the population that is more open to innovation.
• Cold emailing a broad audience may yield a low response rate, with only a small percentage of business owners likely to be interested in adopting AI solutions.

Challenges in Cold Emailing and Effective Inbound Strategies for Early Adopters

• There is a significant handicap (84%) when trying to reach early adopters and innovators through cold emailing, making it challenging to generate interest and responses.
• A low positive reply rate (e.g., 5%) drastically reduces the number of potential clients, leading to minimal engagement from outreach efforts.
• Inbound lead generation methods may be more effective than outbound communications for attracting early adopters, as they allow businesses to draw potential clients to them.
• Creating appealing content for early adopters is essential for successful inbound lead generation.
• Successful strategies for lead generation include utilizing platforms like LinkedIn, Twitter, and YouTube, with an emphasis on focusing on one platform to execute well.

Building AI Agencies through LinkedIn Connections and Content Strategy

• The speaker has successfully built their agency without traditional advertising or outbound communications, relying instead on their content and channel to attract business owners.
• LinkedIn is highlighted as a powerful platform for generating inbound leads, with many successful individuals using similar strategies to connect and engage with potential clients.
• Establishing a base of connections on LinkedIn is essential, and individuals can transition their profiles from previous careers to position themselves as experts in AI solutions.
• Regularly posting valuable content is crucial for demonstrating expertise and building credibility in the AI space.
• There is a race to capture the early majority in the AI agency market, with businesses seeking proof of effectiveness before adopting AI solutions.
• Success in the AI agency space requires obtaining initial clients and evidence of competency to compete with established players in the market.

Low competition in AI agency market and urgency for action

• The AI agency market currently has low competition, with few individuals understanding how to effectively monetize AI services.
• There is a distinction between early adopters, who are excited about AI without needing substantial proof of value, and the early majority, who require evidence-based proof to engage.
• Attracting potential clients through self-selection on platforms like LinkedIn is more effective than direct sales approaches.
• Continuous learning and sharing knowledge can help build trust and establish expertise in the AI space.
• The urgency to act is emphasized, as more competitors are expected to enter the market soon, potentially overshadowing those who delay their efforts.
• A significant update from OpenAI, the assistant API V2 release, is highlighted as an important development in the AI landscape.

Assistance API evolution, enhancements, and early adopter challenges

• The Assistance API is a powerful platform with custom knowledge agents, but it initially faced issues like high costs, slowness, and unreliable knowledge bases.
• The evolution of AI technology parallels the early adoption of the web, where improvements in infrastructure and technology are necessary for broader acceptance.
• The recent update to Assistance API V2 offers enhancements such as increased speed, reliability, and reduced costs, making it more appealing to the early majority.
• Early adopters of AI technology are more focused on its potential rather than practicality, but improvements are needed to attract a wider audience.
• Fine-tuning the Assistance API can tailor it to specific use cases, enhancing its suitability for clients.

AI assistance APIs maturing, early adopters, and client skepticism

• There is a technological advancement in AI, specifically with the development of assistance APIs and conversational pathways, which is maturing rapidly.
• Adoption of new technology lags behind its development, creating a gap that presents opportunities for early adopters.
• The shift in the adoption curve indicates that the early majority will soon embrace the new technology, necessitating quick action from those looking to capitalize on this trend.
• There is skepticism among potential clients due to past experiences with ineffective service providers, which can hinder new solution providers.
• Building a personal brand and sharing experiences is essential for establishing credibility and attracting clients in a competitive market.
• The market for AI solutions is expected to expand significantly, creating opportunities for those prepared to engage with the early majority.

Building AI credibility through testimonials, addressing client objections, and collaborative success

• Establishing credibility through testimonials and case studies is essential for convincing potential clients about the value of AI solutions.
• The speaker emphasizes the importance of addressing pragmatic concerns and objections from clients regarding AI services.
• The speaker's motivation for creating videos is rooted in self-interest; teaching others to succeed will ultimately benefit their own software business.
• Collaboration and shared knowledge among the speaker, their business partner, and the team contribute to the insights shared in the videos.
• The speaker's goal is to help others become successful agency owners, as their success directly impacts the viability of the speaker's software.