82% of companies use AI, but 12% do not measure ROI
Is artificial intelligence delivering on its promise, or is it only creating more noise?
A new approach aims to turn data into real decisions — and measurable outcomes.
The excitement around artificial intelligence now coexists with a quiet frustration: teams are working faster, but not necessarily better. Amid this tension, new solutions are emerging to close the gap between technology adoption and tangible results, a challenge that is becoming increasingly visible across companies in Latin America.
The evolution of artificial intelligence is reshaping how companies grow, but not all tools are delivering real impact. This has intensified challenges across key areas such as marketing, sales, and customer service—from the difficulty of standing out in saturated channels to operational overload within teams and a rising volume of support requests.
Adoption without results.
In Colombia, the landscape reflects this duality. According to the study “Is your AI producing more but not better results?” by HubSpot, based on 201 companies, 82% are already using artificial intelligence to some extent.
However, 12% still fail to demonstrate return on investment, highlighting a growing demand for solutions that translate technological adoption into tangible outcomes.
Against this backdrop, HubSpot announced more than 100 new AI-powered features designed to improve brand awareness, increase revenue, and scale customer support. This approach reflects a fundamental shift: it is no longer enough to process data; tools must understand business context in order to deliver relevant results.
Duncan Lennox, the company’s Chief Product and Technology Officer, states:
”Most AI tools have access to data. What they don’t have is context. Context is far more complex. Data tells you what has happened, while context explains why. It is the dynamic, specific knowledge of your customers, your market, and how your team actually works. That knowledge grows with every interaction, and you can access it whenever you need it. Without context, AI only gives you generic results, but with it, you get real outcomes. This is exactly what we are building.”
New search engines.
Among the key innovations is Answer Engine Optimization (AEO), designed to optimize companies’ presence in AI-driven answer engines such as ChatGPT, Gemini, and Perplexity.
This development responds to shifts in digital behavior: organic traffic has dropped by 27% year over year, while interactions mediated by artificial intelligence continue to grow, creating new opportunities—and challenges—for brands.
The tool enables companies to identify how they appear in these environments, monitor their positioning against competitors, and optimize content through recommendations based on proprietary data. Integrated into Marketing Hub, it also provides prompt suggestions, aiming to reduce uncertainty in optimization.
AI in daily operations.
In marketing, the Breeze assistant is evolving to enable the creation of more context-aware campaigns, helping define audiences and maintain brand consistency. This aims to reduce execution time and improve campaign impact.
In sales, enhancements to the prospecting agent aim to reduce administrative workload and increase efficiency. The tool identifies opportunities based on buying signals, detects key contacts, and generates personalized communications at scale, with results that can double response rates compared to industry averages.
In addition, the intelligent deal progression feature analyzes CRM interactions and data to suggest next steps, update opportunities, and automate follow-ups, enabling more strategic pipeline management.
In customer service, automation is also gaining ground. The customer agent can now handle inquiries continuously, including via email. According to the company, it resolves on average 65% of conversations—and up to 90% in more advanced teams—while also enabling a 25% increase in ticket handling and a 15% reduction in resolution times.
Local context adds further complexity. In Colombia, data privacy (28%) and resistance to change (29%) remain key barriers to AI adoption. In response, these solutions aim to reduce the gap between implementation and real outcomes.
These innovations reinforce HubSpot’s strategy of embedding artificial intelligence across its platform, with an increasingly practical focus: fewer broad promises and more tools designed to deliver measurable results in day-to-day business operations.
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