AI is Already Capable, But Not Yet Commercially Available

The Transformative Impact of Generative AI on Productivity

We are witnessing one of the most significant technological shifts in history. Just as the personal computer revolutionized computing costs and the internet transformed distribution economics, generative AI is rapidly lowering productivity costs across industries.

The Emerging Role of AI in Various Tasks

We anticipate that, in the near future, AI will fully assume a range of tasks, which include, but are not limited to, those outlined below. As every enterprise navigates the integration of AI into their operations, entrepreneurs are discovering unprecedented efficiencies through AI-driven solutions. Whether you are an executive aiming to enhance your company's productivity or an entrepreneur seeking to launch a new venture, there are substantial opportunities in automating these tasks.

Current AI Capabilities and Future Prospects

While significant advancements have been made in AI infrastructure—such as large language models (LLMs), vector databases, and software development tools—the most impactful breakthroughs at the application level are yet to be realized. As AI technology continues to evolve, companies will increasingly productize AI, enhancing its effectiveness across diverse use cases.

Leveraging AI: Immediate Strategies and Frameworks

Evaluating Immediate AI Opportunities

When considering how to leverage AI, whether for incorporating it into existing business processes or developing new AI-based solutions, a useful framework can be as follows:

• Role-Specific AI Agents: For tasks confined to specific roles, AI agents are ideal. These include repetitive, deterministic tasks such as basic data collection, elementary customer service, and document synthesis. AI agents can automate these processes, allowing companies to reduce workforce size or redirect employees to more complex tasks.
  
  

• Vertical AI Software: For tasks within specific industry functions that require decision-making and some ambiguity, vertical AI software can be highly effective. This includes data entry into CRM systems, processes that involve cross-domain interaction, or workflows involving multiple software tools. AI-optimized workflows and industry-specific software can improve efficiency, freeing employees to focus on higher-order tasks.
  
  

• Horizontal AI Software: For tasks that span multiple workflows and support knowledge workers, horizontal AI software is valuable. This includes generating meeting notes, drafting follow-up emails, and reviewing code or wireframes. AI tools designed for horizontal applications can enhance productivity by automating routine tasks, enabling workers to concentrate on creative and complex decision-making.

Examples and Implications

AI Agents Replacing Basic Roles

Certain jobs that involve repetitive and predictable tasks are likely to be largely replaced by AI agents. For instance:

• Compliance Analysts: Tasks such as verifying the authenticity of businesses and ensuring marketing compliance, traditionally performed manually, can now be automated using tools like Parcha or Greenlite. Similarly, AI agents from Norm.ai can review marketing content for regulatory compliance.
  
  

• Sales Development Representatives (SDRs): The automation of lead qualification, data entry, outreach drafting, and pipeline management by tools like 11x allows sales teams to focus more on high-value activities and direct customer engagement.

Implications:

- Companies may reduce headcount in some roles while potentially expanding in others. For instance, companies may employ more account executives if AI handles more top-of-funnel activities.

- AI agents can provide scalable solutions, addressing seasonal or market fluctuations more efficiently than traditional staffing.

- As AI becomes integral to existing back-office functions, new entrants offering targeted AI solutions may challenge incumbent systems. Emerging AI companies could eventually compete with established players by expanding their capabilities.

Vertical AI Solutions Enhancing Efficiency

AI-driven solutions tailored to specific industry functions are transforming traditional processes. For example:

• Healthcare: Tennr automates patient care coordination by processing handwritten documents and integrating relevant information into Electronic Health Record (EHR) systems, enhancing care delivery.
  
  

• Mortgage Lending: Systems like Vesta and Casca automate document processing and communication with borrowers, significantly improving productivity and reducing manual tasks.

Implications:

• New AI companies will likely emerge to address specific, complex pain points previously considered too challenging or costly to automate.
  
  

• Legacy systems, once deemed too entrenched to replace, are now vulnerable to AI-first competitors offering superior performance and efficiency.

Horizontal AI Solutions Enhancing Knowledge Work

AI tools designed for horizontal applications are already providing significant productivity gains. Examples include:

• Meeting Summarization: Granola.so captures and summarizes meeting notes, and may eventually handle follow-up tasks.
  
  

• Automated Workflows: Zapier’s AI capabilities enable the creation of custom workflows across applications, such as automatically updating CRM contacts from calendar entries.

Implications:

• Knowledge workers are experiencing productivity increases of over 20% due to AI. Identifying tasks that could be automated is crucial for further efficiency gains.

The Road Ahead

Although we are still in the early stages of AI adoption, the technology is already delivering substantial productivity improvements. For organizations with domain expertise in processes or workflows that AI can optimize, exploring these opportunities is highly recommended. For larger companies aiming to accelerate their AI integration, evaluating automatable tasks within your organization is a strategic starting point.