The Influence of AI Across Industries

In recent conversation with IT leaders across a range of industries, the topic of business model transformation has come up more than ever due to AI and AI Agents. Most companies are rapidly thinking through what the impact of their business will be in an AI-First world. Not all of the impact will be the same, and it’s clear that industries will evolve in different ways, including how each of the players in these industries adapt with AI. There are a variety of factories to consider, like whether your business model historically sold services by the hour vs. by outcome, how information-centric your product is, the level of critical thinking required to deliver your service, and more. For instance, if you’re a law firm today, AI Agents have the potential of compressing the hours needed for particular legal work. The industry often bills hourly, so fewer hours certainly can put more risk on revenue per account. However, firms are starting to think through multiple ways AI begins to drive growth or benefits firms. You can now expand with more customers because you can deliver more work at a lower rate, or you could deliver even better work in less time, which ironically could mean fees go up even over time. You can extend out this type of dynamic to a variety of other professional services firms, from marketing agencies to systems integrators. Or, take financial services, where large organizations like financial advisory firms are thinking through what AI Agents do to their business model. In this industry, client relationships and value add is the biggest imperative. Even as AI may lower the barrier to getting financial advice for anyone, AI equally provides the potential for even smarter investment decisions and closer customer relationships between the advisor and the client, which leads to greater stickiness. Ultimately, there isn’t a single industry that won’t be impacted in some small or large way due to AI. Some companies will use AI to win more customers, and others will be forced to compete with new AI entrants which deliver services at a lower cost. Not every firm will adapt to this new reality, however, and those will be at the greatest risk. One big implication to all of this transformation is it puts the technology department more in charge of determining the long term business model and execution of a company ever before. The right moves and partnership right now by those implementing AI in their companies are in a critical position to execute on this.

Back in 2008, Garrett Camp and I were walking on the Washington Mall, and he was telling me about this little startup idea he had: "UberCab" The problem was simple—getting a taxi in SF was extremely hard at the time. They called him crazy. People laughed at Brian (AirBnB) for competing with hotels. Oops. The few remaining industries that haven't yet been transformed by technology are about to have their moment. And the legacy players in those industries who like to say "but OUR industry is too human and immune to technology" are about to either adapt, or be replaced. Why? Because AI does heterogeneity and personalization better than humans do. And it does it better than any human ever could at scale - it uses that scale to its advantage. What are some examples? Well, obviously Honor's industry - home care. But let's talk about a few others... 1. Homeowners Association Management This market is incredibly fragmented, with thousands of individual associations. Companies like Anyhoa use AI to automatically manage documents and predict maintenance needs before they become problems. 2. Bookkeeping & Local Accounting Small business accounting remains stuck in manual processes with labor-intensive data entry. AI tools now transfer data from invoices to software, categorize transactions, and generate real-time financial insights. 3. Auto Collision Repair This industry operates on thin margins with variable quality across thousands of independent shops. Companies like Caliber use AI diagnostics to assess damage, streamline estimates, and provide real-time updates to customers. 4. Parking Lot Operations Parking facilities represent massive investments that operate with minimal technology. AI systems use real-time data to optimize parking spaces, automate payment, and enhance security. 5. General Contracting Construction has been notoriously slow to adopt new technologies. But McKinsey estimates AI could boost construction productivity by up to 20% through better planning and resource management. Generative AI alone could add 3.5% productivity growth to the US economy by 2032. That's roughly $1 trillion yearly in economic value. The trillion-dollar question isn't if these industries will transform, but who will lead that transformation. Embrace AI or risk being absorbed. If you're operating in one of these industries, how are you becoming AI native?

Had fun talking “All Things AI” with AiThority.Com’s Rishika Patel recently and exploring how our clients across industries are currently leveraging data-driven analytics and AI to transform their organizations.    Some highlights:    💪🏻Getting data in shape for analytics and AI is one of the biggest challenges our clients face, but it’s also an opportunity to establish a strong framework to optimize the value of #GenerativeAI.    🍏 Organizations are getting started with AI by setting their sights on tactical benefits and gaining value from “low hanging fruit” to build confidence. Others focus their AI initiatives on innovation and growth, while some are testing the waters by embedding AI functionality from major software vendors or SaaS offerings.    🛍️ In retail, AI is making a splash as our clients focus on using AI to streamline business operations and improve customer experiences. For example, AI-powered chatbots and virtual assists are providing personalized support while increasing efficiency and strengthening brand reputation.  (Annika Osterberg)   🏥 Health care is another industry that stands to benefit greatly from GenAI, especially through applications that streamline operations such as the Prior Authorization process. These applications require careful handling of sensitive patient data to maintain compliance and confidentiality. (Bill Fera, Adarsh Gosu, Kumar Chebrolu)   🏭Manufacturing applications for GenAI range from keeping equipment healthy to supply chain optimization. By incorporating GenAI into robotics on factory floors, human workers can focus on innovation and skills development.  (Tim Gaus)   Our Trustworthy AI framework (https://deloi.tt/46Hn5yx) provides underlying guidance on ethical AI development and deployment across industries. It emphasizes safeguards, risk assessment, and continuous monitoring to address ethical challenges. Beena Ammanath, Kate Schmidt, Robert Stradtman   For more on how we are helping our clients leverage AI to solve real-world problems and more advances on the horizon, check out the full Q&A here: https://deloi.tt/3yKgTJm

𝗠𝗬 𝗪𝗘𝗘𝗞 𝗜𝗡 𝗔𝗜: This week’s headlines offered further evidence that AI isn’t just transforming industries – it’s reshaping the very infrastructure that powers them. Developments across AI, robotics, and industrial automation show a shift in development from static infrastructure to dynamic, AI-driven systems that adapt, optimize, and even self-correct in real time. This ongoing transformation presents both opportunities and challenges for business leaders. It will be important to take measured and strategic approaches to adoption. In fact, successful companies will be those that approach AI as an enabler of long-term transformation, not merely a short-term productivity tool. Here’s what stood out for me this week (with some opinion added): 🔹𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗜 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀 𝗠𝗮𝗿𝗸𝗲𝘁 𝘁𝗼 𝗥𝗲𝗮𝗰𝗵 𝗨𝗦𝗗 𝟭.𝟵𝟴 𝗕𝗶𝗹𝗹𝗶𝗼𝗻 𝗯𝘆 𝟮𝟬𝟯𝟭 https://bit.ly/4isZaYz This study follows on the heels of last week’s report of Unilever’s amazing Tinsukia facility. The company is seeing downtime reductions of up to 85%, exemplifying how AI-driven vision systems can streamline production. 🔹𝗗𝗲𝘅𝘁𝗲𝗿𝗶𝘁𝘆 𝗥𝗮𝗶𝘀𝗲𝘀 $𝟵𝟱 𝗠𝗶𝗹𝗹𝗶𝗼𝗻 𝘁𝗼 𝗗𝗲𝘃𝗲𝗹𝗼𝗽 ‘𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗔𝗜’ 𝗳𝗼𝗿 𝗥𝗼𝗯𝗼𝘁𝘀 https://bit.ly/4kQBmzl This news aligns nicely with one of the central themes of next week’s #NVIDIA GTC 2025: "Infrastructure as a Robot." In this world, factories, warehouses, and urban spaces operate as intelligent systems. 🔹𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹—𝗶𝘁’𝘀 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 https://bit.ly/4iQ0Ue6 Companies like #DeepSeek and #Manus are demonstrating how coordinated AI agents can outperform standalone models. The shift mirrors the broader trend in AI-driven infrastructure, where smart grids, autonomous logistics, and adaptive urban planning integrate AI at the system level. 🔹𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗶𝘀 𝗼𝗽𝗲𝗻 𝘁𝗼 𝘂𝘀𝗶𝗻𝗴 𝗻𝗮𝘁𝘂𝗿𝗮𝗹 𝗴𝗮𝘀 𝘁𝗼 𝗽𝗼𝘄𝗲𝗿 𝗔𝗜… https://cnb.cx/3Ft1Gzn Last week we read that tech firms are contracting 48GW of clean energy to power AI growth; this week #Microsoft says it’s open to natural gas. At #GTC25, NVIDIA will likely spotlight AI-driven energy management, with simulation-trained AI agents optimizing grid efficiency and demand forecasting. 🔹𝗢𝗽𝗲𝗻𝗔𝗜 𝘂𝗿𝗴𝗲𝘀 𝗧𝗿𝘂𝗺𝗽 𝗮𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗿𝗲𝗺𝗼𝘃𝗲 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 https://bit.ly/3FG5zB4 The company’s lobbying efforts with the Trump administration reflect yet another industry shift, this time with AI companies pushing for minimal guardrails. Of course, this contrasts with #Anthropic’s call for structured AI governance and highlights the growing tension between scaling #AI and ensuring responsible deployment.

Without doubt, AI innovation is changing the world — across government, business, education, and our everyday lives. Our global AI for Good Impact Report, created by Deloitte and the International Telecommunication Union, explores how AI is helping to advance the United Nations Office for Sustainable Development (UNOSD) Goals (SDG), details where progress is being made, and discusses the risks and challenges associated with AI.     94% of global business leaders view AI as critical to their organizations’ success in the next five years, and many organizations are seeing incredible success from their investments and innovations.  Intriguing applications of AI and GenAI are already hard at work. Here are a few of my favorite examples across industries:    🏥 In healthcare, AI is shifting the focus from treating diseases to early diagnosis and prevention, as smart algorithms identify patterns in digital data and images. Advancements are already making headway in stroke care, cardiology, oncology, and other fields.    📚In education, AI is enhancing the learning experience and improving educational outcomes for students. Intelligent Tutoring Systems use AI to gather data on students, assess their progress, and provide real-time feedback.    🌱 In agriculture, AI helps address food security challenges influenced by climate change. It aids in making real-time crop-placement decisions, monitoring crop health, and enhancing supply chain processes.    💡 In energy, AI models can predict energy consumption patterns, leading to better balancing of supply and demand, reducing waste, and optimizing energy procurement strategies.    🏦 In financial services, AI algorithms identify fraud cases and help prevent financial crimes. AI-driven tools like robo-advisors, digital wallets, and chatbots help to make financial services more accessible to underserved and previously unserved communities.    Explore the report for more innovative use cases that align with SDG goals, as well as recommendations for addressing AI challenges and building an effective governance framework: https://deloi.tt/4hhv6iA