How will artificial intelligence agents evolve in 2026? To help answer this business-linked trend, Digital Journal heard from Andy Sweet, VP of Enterprise AI Solutions, AnswerRocket.
In 2026, AI agents go local
In the final months of 2025, the right conditions converged to support widespread AI agent adoption among small and medium sized businesses. This business segment stands to benefit from AI tools that can enable the productivity they need to automate critical workflows and go head-to-head with major brands.”
In particular, small and mid-sized firms benefit from leaner structures which enables quicker decision-making and implementation. This agility paves the way for such businesses to adapt quickly to new developments, especially to operationalise GenAI.
Nonetheless there are some barriers in the way, which Sweet sees as: “Obstacles like financial investment, technical skills gaps, and limited opportunities to build useful AI agent implementations beyond personal productivity have impeded this potential.”
Rapid technological change has enabled this to take place. According to Sweet: “Now we’re observing a proliferation of tools that democratize this technology (like AI-powered coding tools and agent builders) and early signs that major consumer LLMs may open their interfaces to third-party apps, these technical barriers to implementation are breaking down.”
There are other undercurrents to note: “But more importantly, AI in small business is evolving from individual or point solutions to address more critical workflows. This frees up smaller workforces to apply their creativity to higher-order tasks, potentially opening new lines of business they had not previously been able to offer customers.”
Sweet sets out the beneficial consequence of this: “Due to the flexibility of SMBs and the deep understanding they have of their value to customers, they may be better positioned than larger enterprises to harness these opportunities to reshape their daily operations.”
We’ll trade in AI text chat windows for actual voice conversations
There is something else set to occur during 2026 which businesses need to be mindful of – speech.
AI voice conversation technology has the potential to revolutionise the way businesses and individuals interact with digital systems. At its core, AI voice conversation is about the ability of artificial intelligence systems to engage in natural, human-like spoken dialogues.
With voice AI, Sweet predicts: “While individuals and enterprises primarily engage with AI and AI agents through written text today, we’re going to see voice become dominant in the coming year. Early adopters are already having literal conversations with AI – often to support personal productivity when a written conversation is not feasible. This emerging method of AI communication will also drive innovation in the enterprise.”
Decreasing AI costs in 2026 heralds good news for business
One of the potential developments with business related artificial intelligence during 2026 is with cost reduction. As technology continues to evolve, the opportunities for more firms to take advantage increases.
This is a trend detected by Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket. Greene explains the ‘whys’ and ‘hows’ to Digital Journal.
Cost breaks down as barrier for building great AI models
Greene says that lower-cost AI is something relatively new: “Until recently, it took tons of money to build high-performance AI models, and hefty budgets to run inference on them. But DeepSeek R1 turned that paradigm upside down when it matched the performance of top-tier models at fractions of both training and inference cost. In November, Kimi K2 Thinking topped the benchmarks on Humanity’s Last Exam and BrowserComp, with a reported training cost of only $4.5 million (ChatGPT training runs are estimated at $500 million) and inference cost of $2.50 per million output tokens, one sixth the price of Claude Sonnet 4.5.”
Kimi K2 Thinking is an open-source model that operates as a “thinking agent,” reasoning step-by-step while using tools to achieve state-of-the-art performance on various benchmarks.
Will this tendency continue to be unveiled in 2026? Yes, thinks Greene: “We’ll see this trend intensify in 2026 as more low-cost, high-performance models take off, many of which have open weights.”
What does this cost-reduction mean for the average business venture? Opportunity, summarises Greene: “This completely changes the economics of who gets to play in this space. Suddenly, you don’t need to be a mega-corporation with unlimited capital to build capable AI systems.”
There are also increased prospects for niche markets, as Greene observes: “That shift matters more than people realize because it opens the door for specialized solutions that solve specific, real-world problems instead of trying to be everything to everyone. As more players enter the market with tailored, cost-effective solutions, the competition will push innovation further, enabling industries that were previously out of reach to access powerful AI technology.”
“Open-weight, state of the art” typically refers to the most capable AI models whose parameters (weights) are publicly available for download, use, and fine-tuning, but may not include full training data or code.
In terms of examples, Greene counts: “Open-weight, state of the art models can be run in private clouds, providing the security that CISOs demand for highly regulated industries.”
Democratisation of AI refers to the broad trend of making AI technologies and benefits accessible to more people and organizations.
And as a likely technological predictor for 2026, Greene opines: “This democratization of AI will accelerate the pace at which businesses can address unique challenges and create impactful solutions.”
