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  • How tech buying is changing in 2025–2026 procurement trends reps must know

    How tech buying is changing in 2025–2026 procurement trends reps must know

    How Tech Buying is Changing in 2025–2026: Procurement Trends Reps Must Know

    A salesperson holding a tablet while a buyer points at a clear chart on the tablet

    The landscape of technology procurement is undergoing a seismic shift, and by 2025 and 2026, sales representatives must be keenly aware of the evolving dynamics to stay competitive. Several converging forces, including geopolitical risk, rapid advancements in AI and compute, and the ever-present need for cost optimization, are reshaping how technology buyers make decisions. This article will delve into the key trends shaping technology procurement in 2025–2026, providing actionable insights for tech reps to navigate this new era successfully.

    The Rise of AI-Powered Procurement

    One of the most significant trends shaping procurement in 2025 and 2026 is the pervasive integration of AI. Generative AI and AI-driven solutions are poised to automate various aspects of the procurement workflow, from identifying potential suppliers to negotiating contracts. Technology buyers are increasingly leveraging AI agents to augment their decision-making processes, analyze vast datasets, and gain real-time visibility into the global supply chain. Procurement teams are utilizing AI to forecast demand more accurately, identify potential supply chain risks, and optimize their tech stack. This proactive approach allows them to mitigate disruptions and ensure a resilient supply chain. The 2025 procurement landscape will be defined by organizations that successfully use AI to streamline their processes and unlock new efficiencies.

    Building a Resilient and Visible Supply Chain

    A delivery truck is parked while a worker checks a digital manifest on a smartphone.

    The volatility of the global trade environment, exacerbated by geopolitical risk and increasing cybersecurity threats, has made supply chain resilience a top priority for technology buyers. In 2025 and 2026, procurement teams will prioritize building resilient supply chains that can withstand disruptions. This involves diversifying their supplier base, nearshoring critical components, and implementing robust risk management strategies. Visibility into the entire supply chain ecosystem is crucial. Organizations are investing in technologies that provide real-time insights into supplier performance, inventory levels, and potential bottlenecks. By gaining a comprehensive view of their supply chain, technology buyers can proactively identify and mitigate potential disruptions. The focus is shifting from a reactive approach to a proactive initiative aimed at building a more agile and secure global supply chain. As per Gartner’s

    tech trends report, organizations are actively seeking ways to restructure their supply chains to enhance resilience and minimize the impact of unforeseen events, including potential tariffs and trade wars.

    Data-Driven Decision-Making and Advanced Analytics

    Technology buyers in 2025 and 2026 will rely heavily on data analytics to inform their procurement decisions. The ability to collect, analyze, and interpret vast amounts of data is becoming increasingly critical. Advanced analytics tools are being used to assess supplier performance, identify cost-saving opportunities, and optimize contract terms. Furthermore, organizations are leveraging analytics to gain a deeper understanding of market trends and forecast future demand. This data-driven approach enables technology buyers to make more informed decisions, reduce risk, and maximize value. AI-powered analytics platforms are also helping procurement teams to identify potential third-party risks, such as financial instability or ethical concerns. This enhanced supplier scrutiny is essential for maintaining a responsible and sustainable supply chain. The trends to watch in 2026 indicate a growing emphasis on using analytics to drive continuous improvement in the procurement process.

    Understanding the 2025 Procurement Landscape

    A small team in a meeting room points at a laptop with a bar chart on the screen

    The Role of AI in Procurement

    The procurement landscape in 2025 is being fundamentally reshaped by AI, particularly through the use of agentic AI. Organizations are racing to automate processes and unlock efficiencies through AI adoption, from AI-powered sourcing to contract management. Generative AI and AI-driven solutions are being used to augment human capabilities, enabling procurement teams to make more informed decisions. Technology buyers are increasingly using AI agents to analyze vast datasets, forecast demand, and identify potential supply chain risks. This proactive approach allows them to build resilient supply chains that can withstand disruptions. The 2025 procurement team that successfully uses AI to streamline their workflow and gain real-time visibility into their global supply will have a significant competitive advantage. The ability to use AI and orchestrate cross-functional teams will be critical for success. Stakeholders are increasingly looking to procurement to drive innovation and create value, and AI is a key enabler.

    Key Trends from the Tech Trends Report

    According to Gartner’s tech trends report, a major focus for 2025 and 2026 is the restructuring of supply chains to enhance resilience. This includes diversifying the supplier base, nearshoring critical components, and implementing robust risk management strategies to mitigate global supply chain risks. Analyst data indicates that organizations are actively seeking ways to reduce their reliance on single sources and build more agile and responsive ecosystems. The tech trends report highlights the importance of gaining visibility into the entire supply chain, from raw materials to final delivery. Technology buyers are investing in solutions that provide real-time insights into supplier performance, inventory levels, and potential bottlenecks. By gaining a comprehensive view of their supply chain, they can proactively identify and mitigate potential disruptions. The trends to watch in 2026 and beyond indicate a growing emphasis on using analytics to drive continuous improvement in the procurement process and make data driven decision-making an advantage.

    Impact of Geopolitical Factors on Supply Chain

    Geopolitical risk continues to be a major concern for technology buyers in 2025 and 2026, necessitating robust mitigation strategies. The volatility of the global trade environment, exacerbated by cybersecurity threats and increasing tariffs, has made supply chain resilience and mitigation a top priority. Organizations are prioritizing building resilient supply chains that can withstand disruptions, leveraging advanced technologies for automation and demand forecasting.. This involves diversifying their supplier base, nearshoring critical components, and implementing robust risk management strategies. Visibility into the entire supply chain ecosystem is crucial. Organizations are investing in technologies that provide real-time insights into supplier performance, inventory levels, and potential bottlenecks. By gaining a comprehensive view of their supply chain, technology buyers can proactively identify and mitigate potential disruptions. Many organizations are adopting a more proactive approach to risk management, conducting thorough third-party risk assessments and implementing robust contingency plans. In the current geopolitical climate, supplier scrutiny is more important than ever before.

    Emerging Supply Chain Management Strategies for 2026

    Building a Resilient Supply Chain

    In 2025 and 2026, building a resilient supply chain is not just a goal; it’s a necessity. Technology buyers are looking beyond traditional methods to ensure continuity and mitigate potential disruptions. This proactive initiative involves diversifying the supplier base, investing in nearshoring options, and implementing robust risk management strategies. The focus is on creating a supply chain that can withstand geopolitical risk and cybersecurity threats. Organizations are prioritizing supply chain resilience by gaining better visibility into their entire ecosystem, leveraging analytics to forecast potential issues, and using AI-powered tools to automate responses to disruptions. This approach marks a shift from reactive measures to proactive planning, ensuring the global supply chain remains agile and responsive, and is no longer caught out with tariffs. The ability to use AI to optimize logistics and inventory management will be key for effective supply chain management. The trends shaping procurement in 2025 and 2026 are heavily influenced by the need for greater predictability and control, particularly through automation and demand forecasting.

    Identifying Supply Chain Risks and Compliance Issues

    Identifying and mitigating supply chain risks is critical for technology buyers in 2025 and 2026. Organizations must implement rigorous third-party risk assessments to ensure compliance with regulatory standards and ethical guidelines. The growing complexity of global supply chains necessitates the use of advanced analytics to monitor supplier performance and identify potential vulnerabilities. Geopolitical risk and cybersecurity threats are major concerns, requiring a proactive approach to risk management. Technology buyers are using AI agents to scan for potential disruptions, such as financial instability or ethical breaches among suppliers. The 2025 procurement landscape demands a heightened level of supplier scrutiny to maintain a responsible and sustainable supply chain. By gaining real-time visibility into the entire ecosystem, organizations can quickly identify and address compliance issues. This involves automating monitoring processes and using AI-driven tools to assess supplier performance against key risk indicators. The trends to watch in 2026 indicate a growing emphasis on transparency and accountability within the supply chain.

    Utilizing Generative AI for Procurement Efficiency

    Generative AI is revolutionizing procurement, offering unparalleled opportunities to automate tasks, unlock efficiencies, and enhance decision-making. In 2025 and 2026, technology buyers are leveraging generative AI to streamline workflows, from sourcing and contract negotiation to supplier management. AI-powered tools can analyze vast datasets to identify potential cost savings, optimize contract terms, and forecast demand more accurately. This enables procurement teams to make data-driven decisions and improve overall performance. Generative AI is being used to augment human capabilities, allowing procurement professionals to focus on strategic initiatives and complex problem-solving. The 2025 procurement team is using AI to improve agility and resilience. The trends shaping procurement in 2025 and 2026 indicate a growing reliance on AI to automate routine tasks and accelerate processes. Stakeholders are increasingly looking to procurement to drive innovation and create value, and generative AI is a key enabler. Effective use cases include AI agents to automate various aspects of the procurement workflow and providing actionable data to optimize supply chain management.

    Trends to Watch in 2026

    Cybersecurity Challenges in Procurement

    In 2025 and 2026, cybersecurity threats are a growing concern for technology buyers, and organizations need a proactive approach to protect their supply chain. As technology evolves, so do the risks associated with it, and cybersecurity must be prioritized. With increased geopolitical risk, there’s a growing awareness of third-party vulnerabilities that could compromise sensitive data and disrupt operations. Technology buyers must conduct thorough risk assessments of their suppliers to ensure they meet cybersecurity standards. This involves verifying security protocols, conducting regular audits, and implementing robust incident response plans to enhance mitigation efforts. The trends shaping procurement in 2025 and 2026 reflect an increased focus on resilience and risk management in the face of these threats. Organizations will need to invest in tools and technologies that provide real-time visibility into potential security breaches and automate responses to mitigate risks. By prioritizing cybersecurity, technology buyers can protect their organizations from costly disruptions while leveraging agentic AI to maintain trust with stakeholders. Analysts at Gartner are pointing towards a proactive approach regarding these factors.

    Reshaping Supplier Relationships under Cost Pressure

    The 2025 and 2026 procurement landscape is also heavily influenced by cost pressure, forcing technology buyers to rethink their supplier relationships. Organizations are under constant pressure to reduce costs while maintaining quality and innovation. This is leading to a greater emphasis on strategic sourcing and value engineering. Technology buyers are seeking to build collaborative partnerships with suppliers, where both parties work together to identify cost-saving opportunities. This involves sharing data, jointly developing solutions, and aligning incentives. As the global trade environment becomes more uncertain, technology buyers need to build resilience into their supply chains. This means diversifying their supplier base and implementing robust risk management strategies for effective mitigation. By focusing on total cost of ownership and building strategic partnerships, technology buyers can optimize their supplier relationships and drive greater value for their organizations through automation. Organizations are looking for suppliers who can offer innovative solutions and competitive pricing to help them achieve their financial goals. Cost is always a factor but as Gartner and analysts are reporting, resilience and automation must be part of the equation as well.

    Insights from Gartner on Future Trends

    According to Gartner’s

    latest tech trends report, several key themes will dominate the procurement landscape in 2026 and beyond. In particular, technology buyers will focus on:

    • The use of AI becoming more pervasive, automating tasks, augmenting decision-making, and unlocking new efficiencies.
    • Data-driven decision-making becoming even more critical, with buyers relying on analytics to inform their procurement strategies.

    These insights highlight the importance of embracing new technologies, building strong supplier relationships, and staying ahead of emerging risks. By understanding these trends shaping procurement, sales representatives can better position themselves to meet the needs of technology buyers and drive successful outcomes in 2025 procurement and 2026. Reshaping, restructuring, and reimagining supply chain management is now a must for all, and the trends to watch in 2026 can help to unlock new strategies and solutions.

  • From copilots to agentic selling: what to automate vs. what must stay human

    From copilots to agentic selling: what to automate vs. what must stay human

    From copilots to agentic selling: what to automate vs. what must stay human

    A seller watches a laptop with a toy robot next to the keyboard

    The rise of artificial intelligence in sales has brought forth various tools aimed at boosting productivity and streamlining workflows. Among these, AI copilots and agentic AI stand out, each offering unique capabilities. While AI copilots augment human abilities by assisting with specific tasks, agentic AI represents a leap towards autonomous systems capable of making decisions and executing multi-step processes with minimal human intervention. This article explores the main differences between agentic AI and AI copilots, highlighting what to automate and what requires the irreplaceable touch of a human agent.

    Understanding Agentic AI

    What is Agentic AI?

    Agentic AI refers to autonomous AI agents that can perform specific tasks from start to finish without constant human input. Unlike traditional AI systems that require a prompt for each action, agentic AI can make decisions and execute actions based on predefined goals and real-time data. This advanced AI possesses a level of autonomy, enabling it to adapt and learn within its defined framework. These AI tools are designed to handle complex agentic workflows, freeing up human agents to focus on higher-level strategic activities, driving productivity gains, and optimizing overall team performance. Agentic AI systems represent a significant step forward in enterprise AI solutions.

    Key Differences: Agentic AI vs AI Solutions

    The key differences between agentic AI and AI copilot solutions lie in their level of autonomy and decision-making capabilities. AI copilots serve as assistants, providing real-time support and suggestions to human agents. This can be further understood by comparing their characteristics in the context of how agentic AI comes into play.

    Feature AI Copilot Agentic AI
    Decision-Making Requires human oversight to make final decisions and continue workflows. Can make decisions and act independently to achieve specific goals.
    Autonomy Augments human capabilities by automating repetitive tasks and providing insights, but always requires human oversight. Can handle multi-step processes and autonomously complete tasks, such as prospecting or lead nurturing, with only periodic human oversight.

    This distinction highlights the shift from AI as a tool to AI as an autonomous agent, with the potential to significantly impact AI adoption as agentic AI is designed to enhance efficiency.

    Use Cases for Agentic AI

    The use cases for agentic AI span various aspects of sales and customer support, showcasing its potential to automate complex workflows without the need for extensive human input. Agentic AI can make decisions, nurture leads through personalized email sequences, schedule follow-up calls, and update CRM data, all autonomously. In customer support, agentic AI can resolve common issues, process returns, and escalate complex inquiries to human agents. Agentic workflows in sales can involve identifying high-potential leads and personalizing outreach strategies, while in marketing, agentic AI can manage ad campaigns and optimize content based on performance metrics. Choosing the right AI solution, whether an AI copilot or agentic AI, depends on the specific tasks and the level of autonomy desired, with the understanding that human intervention remains crucial for ethical considerations and complex problem-solving.

    The Role of AI Copilots

    A group of people in a meeting room look at a large display with a half-robot, half-human face image

    What are AI Copilots?

    AI copilots are designed to augment human capabilities by providing real-time assistance and automating specific tasks. Unlike agentic AI, which operates autonomously, AI copilots require human input to initiate actions and make decisions. These AI tools act as intelligent assistants, offering suggestions and insights to streamline workflows. They enhance productivity by handling repetitive tasks, such as data entry, scheduling, and generating reports, allowing human agents to focus on more strategic and complex activities. In essence, AI copilots work alongside human agents, providing support and guidance to improve efficiency and decision-making. AI copilots contribute to productivity gains and support better outcomes.

    Benefits of Using AI Copilots

    The benefits of using AI copilots are numerous, particularly in enhancing productivity and improving the efficiency of human agents. AI copilots can automate many of the routine tasks that consume a significant amount of time, such as data entry, email management, and report generation. This automation frees up human agents to focus on more strategic activities, such as building relationships with customers, closing deals, and developing innovative solutions. AI copilots also provide real-time insights and recommendations, helping human agents make better decisions and avoid costly errors. By integrating AI copilots into their workflows, businesses can improve overall performance and achieve significant productivity gains. AI adoption of these copilots enhances existing workflows.

    Choosing the Right AI Copilot

    Choosing the right AI copilot involves evaluating your business needs and identifying specific tasks that can benefit from automation. Assess your current workflows to pinpoint areas where AI can improve efficiency and decision-making. Look for AI copilots that offer features tailored to your industry and business processes. Ensure the AI copilot is easy to integrate with your existing systems, such as CRM and email platforms. Consider the level of human oversight required and choose an AI copilot that aligns with your desired level of autonomy. Additionally, evaluate the AI copilot’s ability to learn and adapt to your changing needs, as agentic AI is changing the landscape of business operations. By carefully considering these factors, you can select an AI copilot that delivers significant productivity gains and enhances the performance of your human agents.

    Automation vs Human Touch

    What to Automate in Sales Processes

    Identifying what to automate in sales processes is crucial for maximizing productivity gains. AI agents, particularly agentic AI, are well-suited for handling repetitive, data-driven specific tasks. These include agentic AI features that enhance automation and improve customer satisfaction. lead scoring, data entry into CRM systems, and initial customer outreach. Agentic AI can automate personalized email campaigns, scheduling follow-up actions based on prospect behavior, and updating contact information. These agentic workflows free up human agent time to focus on building relationships and closing deals. By leveraging AI tools for these specific tasks, sales teams can significantly improve efficiency and reduce manual errors. Choosing the right AI solution allows for seamless automation in sales processes, leading to increased revenue and better resource allocation. Businesses can adopt AI to eliminate mundane tasks and empower sales representatives with more time for strategic activities.

    Tasks That Require Human Interaction

    While agentic AI and AI copilots excel at automation, certain tasks inherently require human intervention. Complex negotiation, building trust with key clients, and understanding nuanced customer needs are areas where human agent skills are irreplaceable. Human oversight is essential in resolving intricate customer issues that autonomous systems cannot handle effectively. Empathy, critical thinking, and the ability to adapt to unique situations are key attributes that human agent brings to the table. AI systems can provide insights and suggestions, but the final decision-making and the ability to handle sensitive situations require a human agent. These interactions build stronger relationships and foster customer loyalty. Human input remains crucial for ethical considerations, complex problem-solving, and maintaining the personal touch that customers value.

    Balancing Automation and Personal Touch

    Finding the right balance between automation and personal touch is essential for successful sales and customer support. The best approach involves strategically integrating AI copilots and agentic AI to enhance, rather than replace, human agent interactions. Agentic AI can handle initial outreach and lead qualification, while human agent take over for in-depth conversations and relationship building. AI adoption should focus on automating routine tasks, freeing up human agent to focus on strategic initiatives and personalized customer support. Regular oversight of autonomous AI agents ensures that they align with company values and customer expectations. Real-time data and analytics from AI systems can inform human agent actions, leading to more effective and personalized interactions. By carefully considering the strengths of both AI tools and human agent, businesses can create a seamless and effective sales process that delivers exceptional customer experiences. Main differences between agentic ai and ai copilots need to be considered.

    Implementing Autonomous AI in Workflows

    A person at a desk gives a paper to a small robot and keeps a pen in their other hand

    Framework for Incorporating Autonomous AI

    A structured framework is crucial for successfully incorporating autonomous AI into existing workflows. Implementing agentic workflows effectively requires careful consideration of several key steps, including:

    1. Identifying specific tasks ripe for automation through AI tools. This assessment should pinpoint processes that are repetitive, data-driven, and require minimal human intervention.
    2. Choosing the right AI solution entails evaluating various AI systems and agentic AI platforms based on their capabilities and integration potential.

    It also involves setting clear goals and parameters for AI agents, defining their scope of autonomy, and establishing human oversight mechanisms to ensure alignment with business objectives. Real-time monitoring and feedback loops are essential for continuously improving the performance of autonomous AI agents, and ensure that agentic ai can make actions based on the predefine set of rules.

    Decision-Making with AI Agents

    AI agents enhance decision-making by processing vast datasets and identifying patterns that human agent might miss. Unlike traditional AI, agentic AI can make decisions and execute multi-step processes autonomously, based on predefined goals and real-time data. However, human input remains crucial for ethical considerations and complex problem-solving. AI tools can provide insights and recommendations, but agentic AI goes beyond that by automating decision-making processes. human oversight is essential for ensuring that decisions align with company values and customer expectations. Implementing AI copilots alongside agentic AI allows for a balanced approach, where AI handles routine tasks without the need for constant human intervention. decision-making, and human agent focus on strategic and nuanced situations. Main differences between agentic ai and ai copilots are highlighted in critical thinking and empathy towards customers. As a result, businesses can adopt ai and improve the quality and speed of decision-making across various functions, improving productivity gains.

    Future of Work with Agentic Workflows

    The future of work envisions a seamless integration of agentic AI into daily workflows, transforming how businesses operate. As AI adoption increases, specific tasks will become fully automated, enabling human agent to focus on creativity, innovation, and relationship building. Agentic systems can handle customer support, freeing up human agent to address complex issues and build stronger customer relationships. The rise of autonomous AI agents will also require new skills and training programs for employees to effectively work alongside agent copilots. human agent, focusing on collaboration with AI tools and human oversight of AI decision-making. The key differences of agentic ai vs ai will blur as AI continues to improve. Businesses can deploy ai agents to augment and amplify the impact of human agent. With the integration of agentic AI, businesses can enhance their operational efficiency and improve customer satisfaction. advanced ai in the enterprise ai, the framework will emphasize ethical considerations, transparency, and continuous monitoring to ensure that autonomous AI aligns with societal values and business goals, ensuring that agentic AI contributes positively to customer satisfaction.