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While most apps require the user to locate the feature they need, SuperCity will soon present itself as a conversational bot. A resident will simply discuss what they need and the app will use AI agents to carry out as much of the need with little, if any, user engagement. Removing integration complexity also means that this single app can be used by a user in different cities without requiring the download of a new app with an entirely different process. The team behind SuperCity come with significant government and technology credentials.<\/p>\n<\/p>\n
Akoum noted that 40 percent of the people who visit the site have been using the model, leading to a rise in engagements and folks taking the next step in the transaction. In addition, while AI agents must also comply with the European Union\u2019s AI Act and similar regulations, innovation will quickly outpace those rules. Businesses must not only ensure compliance but also manage various risks, such as misrepresentation, policy overrides, misinterpretation, and unexpected behavior.<\/p>\n<\/p>\n
Humans can also understand neighborhood dynamics of a specific property market that may not be evident in real estate data. In contrast, AI may not fully understand the impact of local market conditions, neighborhood dynamics, zoning regulations or specific property features that can significantly influence overall investment decisions. Such trust also needs to be managed \u201cintuitive human-AI collaboration, ensuring efficiency while preserving user authority,\u201d said Srivastava. Without trust and confidence, agentic AI systems\u2019 ability to autonomously plan, reason, and execute tasks will be irrelevant. \u201cStriking this delicate balance will be crucial for the long-term success of AI-driven businesses,\u201d he said.<\/p>\n<\/p>\n
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Matt Coatney, CIO of business law firm Thompson Hine, said his organization is already actively experimenting with agents and agentic systems for both legal and administrative tasks. \u201cHowever, we are not yet satisfied with their performance and accuracy to consider for real-world workflows quite yet,\u201d he said, adding that the firm is focused on agent use in contract review, billing, budgeting, and business development. Unlike a large language model (LLM) or generative AI (genAI) tools, which usually focus on creating content such as text, images, and music, agentic AI is designed to emphasize proactive problem-solving and complex task execution, much as a human would. The survey of 300 senior executives, released by PwC last month, finds evidence of these basic benefits, as well as plenty of money flowing toward agents. Almost all, 88%, say their team or business function plans to increase AI-related budgets in the next 12 months to develop and deploy agentic AI. Seventy-nine percent say AI agents are already being adopted in their companies.<\/p>\n<\/p>\n
The rise of AI agents is not just another incremental improvement\u2014it is a fundamental shift in how businesses operate. The enterprises that embrace AI agents now will be the ones shaping the future, setting new industry standards and outperforming their competitors in the years to come. Daniel Fallmann is founder and CEO of Mindbreeze, a leader in enterprise search, applied artificial intelligence and knowledge management. While Realtors could hire someone to digitally stage a room using tools like Photoshop, Virtual Staging AI promises a cheaper and faster way to do so. The startup\u2019s cheapest plan costs $12 per month and includes six photos, while the most expensive plan costs $69 per month and comes with 250 photos. Realtors can also use the tool to remove furniture from images and replace it with different furniture.<\/p>\n<\/p>\n
I\u2019ve found that embracing a human-AI partnership\u2014in which human, investor expertise complements AI\u2019s intelligent capabilities\u2014is the best way forward for the commercial real estate sector. At the company I co-founded where I serve as CEO, we are disrupting commercial real estate by integrating AI, machine learning and data science into traditional real estate investing. We take an end-to-end comprehensive approach to our AI application, allowing us to source, underwrite, buy, sell and manage assets on behalf of our investors. Supporting real estate agents in becoming more productive is even more relevant in the context of changes to the commission structure. With a career spanning more than two decades in journalism and technology research, Lucas Mearian is a seasoned writer, editor, and former IDC analyst with deep expertise in enterprise IT, infrastructure systems, and emerging technologies.<\/p>\n<\/p>\n
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For instance, if an image includes mismatched furniture, the startup\u2019s tool can remove it and replace it with modern furniture. The startup\u2019s tool allows Realtors to add furniture to images of empty rooms within seconds. Instead of having to share images of empty rooms in a listing, the tool gives Realtors realistic images of furnished rooms. Realtors can choose to turn an empty room into a bedroom, living room, office, playroom, etc.<\/p>\n<\/p>\n
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They don\u2019t just wait for instructions; they proactively surface insights, automate repetitive tasks and help teams focus on what really matters\u2014solving complex problems and driving strategic initiatives. Their ability to continuously learn and adapt ensures they become more valuable over time, making them an indispensable asset for any modern enterprise. With AI, buyers can search for properties by describing their dream home using ChatGPT or sharing images, rather than using traditional filters on platforms such as number of bedrooms and bathrooms, McLaughlin says. It could also identify neighborhoods or properties that buyers may not have discovered otherwise. Sellers can use AI to help compare the cost and estimated return of presale renovation projects. And some brokerages are utilizing it to review agents\u2019 past transactions and see what steps they took that generated more sales or higher profits, McLaughlin says.<\/p>\n<\/p>\n