For years, conversation about artificial intelligence (AI) in companies has focused almost exclusively on cost reduction. However, the data show a disturbing reality: although more than 78 % of organizations already use generative in some function, less than 20 % see a real impact on their income and only 1 % consider that their strategy is mature, according to a recent McKinsey report. The paradox is evident: it is reversed in AI, but the fruits are not collected.
With the aim of responding to this gap, the Aissist.io company has launched a new Whitepaper titled Manual for AI leaders: unlocking growth beyond cost reduction. The document, based on more than 300 global projects, not only diagnoses the causes of stagnation, but also offers an action framework for companies to make the adoption of the measurable growth.
Mentalities and traps that stop the impact of AI
The study identifies two great errors that explain why so many organizations remain halfway: address the AI only as a savings tool and display it in silos, without interfunctional integration. “The AI is not failing because the technology is weak. It is failing because companies address it with too limited objectives,” says Lifan Xu, co -founder of Aissist.io. “When AI is focused only as a cost reduction tool, a much greater opportunity is lost: unlock new income flows, scalability and business models.”
The document collects figures that support your vision. Among the deployments made by Aissist.Io, an 83 % automation in “digital employees”, 70 % traffic resolution without human intervention and increases of up to 50 % in sales conversions were reached. In addition, the projects registered a customer satisfaction rating (CSAT) of 4.8 points and reductions of 50 % in high volume operations costs.
Although more than 78 % of organizations already use generative in some function, less than 20 % see a real impact on their income and only 1 % consider that their strategy is mature
The pressure to demonstrate ROI in 2025
The year 2025 is emerging as a turning point. With the adoption of AI generalizing at high speed, management councils and investors are raising pressure to demonstrate clear returns. The experiments that do not climb cease to be acceptable and business leaders face the need to translate innovation into tangible business metrics.
The Aissist.io manual emphasizes that the key is in passing cases isolated to interfunctional deployments and growth -oriented. The AI, applied in a transverse way and linked to income objectives, can cease to be a expensive experiment to become a transformation engine.
Real cases: from growth automation
Whitepaper offers concrete examples that illustrate how companies can go beyond savings.
- A global telecommunications provider managed to automate customer service and unlock an additional million dollars in monthly income by increasing its sales conversion rate from 32 % to 42 %.
- A realized real estate group in commercial real estate automated 95 % of its sales funnel, which allowed the launch of a new business line.
- A chain of vehicle repair workshops integrated with complex diagnoses, drastically reducing budgeting times and expanding their capacity beyond what human agents could assume.
These examples show that the AI not only lightens operational loads, but can become a direct lever of new income and scalable business models.
A four stages frame for success
The report closes with a four -phase roadmap that synthesizes the lessons learned:
- Establish interfunctional leadership in AI, which aligns business areas with technology.
- Define clear metrics from the beginning, not only for savings, but of growth.
- Find a simultaneous impact on income and costs, expanding the strategic focus.
- Automate beyond basic interactions, incorporating complex and added value processes.
This approach, according to Aissist.io, is the one that will make the difference between the organizations that simply experience with AI and those that manage to transform their business model in the coming years.
