Why Your Next Funding Round May Hinge On Well-Managed Human-Agentic AI Collaboration
By Imran Aftab
Venture capitalists are investing heavily in autonomous systems powered by agentic AI, signaling a new era of technological innovation. In the first month and a half of 2025, European VCs allocated a whopping $548 million to AI agent startups.
Versions of agentic AI systems have existed for years, but the recent advancements in natural-language capabilities have unveiled new horizons. We’re transitioning from simple GenAI-powered tools to autonomous “agents” that can perceive, strategize and act independently.
They can work with existing software tools and platforms to complete tasks, collaborate with other agents and people, and learn to enhance their own performance.
However, that money isn’t going to those who have great ideas about agentic AI. Investors are looking at the founders who have nailed implementation and risk management, locked in a clear pathway to ROI, and are building agentic AI infrastructures with humans at the center.
They want to see AI agents’ quantifiable impact on business processes. How much are these tools boosting productivity to generate revenue gains? How has an AI agent enhanced customer relationships to drive loyalty and how does this translate into the bottom line? It’s these base metrics that can make or break your business case for funding.
A solid data foundation is crucial
Next, keep in mind that investors aren’t just betting on an algorithm; they’re betting on your data integrity. Last year, major tech players including Google, Microsoft, OpenAI and others made investments in frameworks to enable agentic functionality.
We’ve seen the same trends with our clients: They’re leveraging AI for business efficiency. However, despite advancements, they continue to grapple with data quality problems like data silos, biased datasets and inaccurate inputs.
AI built on shaky data foundations is only going to cause problems. Poor data management severely impacts the effectiveness and financial returns of their AI initiatives, and that will send VCs running.
Prove that your data is clean, verified and strongly governed so that your AI outcomes are as solid as your data management.
Human oversight still matters
Yet the right agentic AI framework is unattainable without a human touch. There is no scenario where humans can be completely removed from the equation. Companies capturing the most value from agentic AI often revamp their business processes to embed AI solutions while incorporating human-guided validation of AI models and results.
In fact, human oversight of data quality and architecture directly impacts a startup’s attractiveness to VCs.
According to a McKinsey survey published in March 2025, organizations are “ramping up their efforts” to manage AI risks related to inaccuracy, cybersecurity and more. To be ahead of the game, drive agentic AI adoption, and attract funders, organizations need to onboard domain experts and high-quality talent while driving education about security best practices.
Organizations must then also create a seamless relationship between human insight and AI capabilities. The very human role of strategic decisionmaking and creative design thinking is needed to mitigate AI’s inherent risks and respond to failures and breaches when they do happen. According to the BCG AI Radar global survey, top-performing organizations follow the 10-20-70 principle too, dedicating 70% of time to “people, processes, and cultural transformation,” which, in turn, could de-risk investment.
This principle should apply as companies introduce AI agents since employees’ human touch is crucial for ensuring accountability and security. Despite agentic AI’s design to autonomously decide and act on complex processes, senior leaders must maintain strategic oversight to ensure that these decisions align with wider strategic goals.
And let’s face it: Mature human-AI collaboration is a key indicator of an investable startup.
Imran Aftab is the co-founder and CEO of 10Pearls, an AI-powered global technology partner that helps businesses innovate, digitalize and scale. Under his leadership, 10Pearls has grown into a world-class organization with more than 1,300 employees across four continents. 10Pearls empowers clients with cutting-edge solutions in digital transformation, AI and software development, enabling them to accelerate growth and enhance operational efficiency. The company partners with businesses to drive innovation and deliver impactful, scalable technologies across industries.
Illustration: Dom Guzman
Read More
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Why Your Next Funding Round May Hinge On Well-Managed Human-Agentic AI Collaboration
By Imran Aftab
Venture capitalists are investing heavily in autonomous systems powered by agentic AI, signaling a new era of technological innovation. In the first month and a half of 2025, European VCs allocated a whopping $548 million to AI agent startups.
Versions of agentic AI systems have existed for years, but the recent advancements in natural-language capabilities have unveiled new horizons. We’re transitioning from simple GenAI-powered tools to autonomous “agents” that can perceive, strategize and act independently.
They can work with existing software tools and platforms to complete tasks, collaborate with other agents and people, and learn to enhance their own performance.
However, that money isn’t going to those who have great ideas about agentic AI. Investors are looking at the founders who have nailed implementation and risk management, locked in a clear pathway to ROI, and are building agentic AI infrastructures with humans at the center.
They want to see AI agents’ quantifiable impact on business processes. How much are these tools boosting productivity to generate revenue gains? How has an AI agent enhanced customer relationships to drive loyalty and how does this translate into the bottom line? It’s these base metrics that can make or break your business case for funding.
A solid data foundation is crucial
Next, keep in mind that investors aren’t just betting on an algorithm; they’re betting on your data integrity. Last year, major tech players including Google, Microsoft, OpenAI and others made investments in frameworks to enable agentic functionality.
We’ve seen the same trends with our clients: They’re leveraging AI for business efficiency. However, despite advancements, they continue to grapple with data quality problems like data silos, biased datasets and inaccurate inputs.
AI built on shaky data foundations is only going to cause problems. Poor data management severely impacts the effectiveness and financial returns of their AI initiatives, and that will send VCs running.
Prove that your data is clean, verified and strongly governed so that your AI outcomes are as solid as your data management.
Human oversight still matters
Yet the right agentic AI framework is unattainable without a human touch. There is no scenario where humans can be completely removed from the equation. Companies capturing the most value from agentic AI often revamp their business processes to embed AI solutions while incorporating human-guided validation of AI models and results.
In fact, human oversight of data quality and architecture directly impacts a startup’s attractiveness to VCs.
According to a McKinsey survey published in March 2025, organizations are “ramping up their efforts” to manage AI risks related to inaccuracy, cybersecurity and more. To be ahead of the game, drive agentic AI adoption, and attract funders, organizations need to onboard domain experts and high-quality talent while driving education about security best practices.
Organizations must then also create a seamless relationship between human insight and AI capabilities. The very human role of strategic decisionmaking and creative design thinking is needed to mitigate AI’s inherent risks and respond to failures and breaches when they do happen. According to the BCG AI Radar global survey, top-performing organizations follow the 10-20-70 principle too, dedicating 70% of time to “people, processes, and cultural transformation,” which, in turn, could de-risk investment.
This principle should apply as companies introduce AI agents since employees’ human touch is crucial for ensuring accountability and security. Despite agentic AI’s design to autonomously decide and act on complex processes, senior leaders must maintain strategic oversight to ensure that these decisions align with wider strategic goals.
And let’s face it: Mature human-AI collaboration is a key indicator of an investable startup.
Imran Aftab is the co-founder and CEO of 10Pearls, an AI-powered global technology partner that helps businesses innovate, digitalize and scale. Under his leadership, 10Pearls has grown into a world-class organization with more than 1,300 employees across four continents. 10Pearls empowers clients with cutting-edge solutions in digital transformation, AI and software development, enabling them to accelerate growth and enhance operational efficiency. The company partners with businesses to drive innovation and deliver impactful, scalable technologies across industries.
Illustration: Dom Guzman
Read More