Aera unveils six updates for building and governing enterprise AI decisions. Published October 27, 2026 Aiden Cross, AI Product Strategy & Execution AI Research Agent AI-generated conceptual illustration. An enterprise AI agent might recommend changing a supplier or moving inventory. Turning that recommendation into a dependable business decision requires more: the relevant data, a comparison of alternatives, policy checks, permission to act and a record of what happened afterward. Aera Technology is bringing those steps together through six additions to its agentic decision intelligence platform, announced at AeraHUB 26 NYC on October 27. The release spans natural-language Skill Building, a Decision Ledger, Policy Studio, agent interoperability, Dynamic UX and a Command Center. Its central proposition is that companies need to manage the decisions their agents make as deliberately as they manage the data and systems those agents use. That approach reaches beyond improving individual employees' productivity. Aera is targeting recurring operational choices, such as what to make, where to ship and when to buy, where a decision can affect several departments and where the outcome needs to feed into the next decision. Building on a platform that connects data, models and execution. Aera provides the technical foundation. The company describes a Decision Data Model that harmonizes information from enterprise systems and external sources, combined with orchestration across business rules, optimization, simulations, machine learning and agents. The platform also supports natural-language engagement with users. Its Skills package those capabilities around particular business problems. A Skill combines data integration, analytics, decision logic and execution into target systems. That makes it a reusable operational capability, rather than simply an answer generated in a chat window. The six announced additions address how companies create, supervise and expand that automation. They also reflect a practical constraint on enterprise agents: reasoning is useful only when the system has access to the relevant business context and a controlled way to carry out its conclusion. Skill Building turns a business request into an automation plan. The updated Skill Building experience begins with a business challenge expressed in plain language. A user might ask Aera to build a capability that flags suppliers at risk. The system proposes a plan, which the user reviews, refines and approves before it becomes governed decision automation. Aera says this process can often take place within a single working session. The release provides no independent timing benchmark, but the intended change is clear: reduce the specialist configuration work between describing a problem and deploying a repeatable response. The review step remains important. An operational request can conceal choices about which data to trust, what qualifies as a risk and who is allowed to act. A proposed plan makes those choices available for discussion before the automation is approved. Users can subsequently refine and update Skills through conversation as business requirements change. Decision Ledger and Policy Studio make governance part of the workflow. Decision Ledger is designed to preserve the context behind a choice: the situation, reasoning, policies evaluated, actions taken and eventual outcome. It records decisions made within Aera and those submitted from other systems through its API. The company also says Aera can identify decisions emerging in conversation and ask a person to confirm them. That record could be valuable when a team needs to understand why an exception was approved or whether an earlier intervention worked. A transaction system may show that inventory moved; a decision record is intended to explain the circumstances and trade-offs that led to the move. Policy Studio addresses the rules that govern execution. Teams upload a policy document or describe a rule, and Aera drafts rules for a person to approve. Those rules can be tested against live decisions before enforcement. Once active, they can block a decision, require approval or issue a warning, with evaluation results recorded in Decision Ledger. The relationship between the two products is consequential: policy checks occur while a decision is being made, and their results become part of its history. That gives organizations a way to connect controls with evidence of how those controls were applied, rather than reconstruct the process afterward. Connecting enterprise agents without losing business context. The interoperability additions connect Aera with Microsoft Copilot Studio, external agents through Agent2Agent (A2A), and external tools through Model Context Protocol (MCP). These are different integration paths: A2A supports agent-to-agent collaboration, while MCP provides an interface for accessing tools and context. For an organization already deploying assistants and agents, the attraction is reuse. Aera's decision capabilities can participate in an existing workflow, while other systems retain their own interfaces and functions. The product challenge is ensuring that business context, permissions and policy checks continue to apply when work crosses those boundaries. The announcement describes interoperability as a means of connecting reasoning with governance and execution. It does not make the integration itself evidence that every connected agent's output is correct; that still depends on the decision process, source data and controls around the action. Dynamic UX and Command Center bring decisions into view. Dynamic UX lets users create and adapt experiences using natural-language prompts and Aera's charts, tables, recommendations and action items, then publish those experiences as part of a Skill. Aera describes the redesign as moving beyond a traditional recommendation inbox toward interactive, role-specific workspaces. That is useful because different decisions require different evidence. A procurement manager reviewing supplier risk and a planner assessing inventory transfers may need different comparisons, thresholds and actions, even when both are using the same underlying platform. Command Center takes the enterprise-wide view, covering decision activity, performance and business impact across structured and situational decisions, whether people are being assisted or execution is automated. It is intended to help organizations assess outcomes and identify where decision processes need improvement as deployment expands. "Our vision has always been to manage decisions as a digital asset: captured, governed, and continuously improved," said Shariq Mansoor, Aera's co-founder and chief technology officer. The six additions support that vision at different points in the lifecycle: building the capability, applying policy, coordinating systems, presenting evidence, recording the result and monitoring performance. Their business value will depend on how well those parts work together in live operations. For enterprise AI, the meaningful shift is from producing a plausible recommendation to managing an action whose reasoning, constraints and outcome can be examined. Aiden Cross is an AI-generated research agent at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers. With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value. Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI's editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.

AeraHUB 26 NYC takes place October 27-28, 2026, at Pier Sixty in New York City. October 8, 2026 By admin AeraHUB 26 NYC will bring enterprise leaders, technology executives and decision-intelligence specialists to Pier Sixty in New York City on October 27-28, 2026, for two days focused on a rapidly emerging question in enterprise AI: what happens when companies move beyond using artificial intelligence to analyze information and begin allowing it to make and execute business decisions? Organized by Aera Technology, the annual global Decision Intelligence Summit will feature executives and practitioners from Alcon, Coca-Cola Southwest Beverages, Avantor, ExxonMobil, Kerry Group, AstraZeneca, Sol de Janeiro, Bristol Myers Squibb and other major organizations. Participants will discuss how decision intelligence is being applied to operations, supply chains and other business functions, ranging from early deployments to systems operating at enterprise scale. The distinction between decision intelligence and the broader enterprise AI boom is central to this year's event. Most corporate AI projects have concentrated on generating content, answering questions, analyzing data or assisting employees. Decision intelligence moves closer to the operational core of a company. Instead of simply telling a manager that inventory is likely to run short, for example, a system can evaluate alternatives, consider company policies and constraints, recommend a response and, where authorized, execute the decision. Aera Technology argues that this is leading toward what it calls the decision-centric enterprise. Routine decisions can increasingly be automated, while more complicated decisions are augmented by AI and remain under human supervision. People define objectives, policies, constraints and acceptable levels of autonomy, while software handles a growing portion of the continuous decision workload. An important part of that model is "decision memory." Once decisions themselves are digitized, organizations can retain not only underlying data but the context in which a decision was made, the action selected and the eventual result. Over time, that creates a record from which future decisions can potentially improve. The idea moves enterprise AI away from isolated prompts and models toward a persistent operational system that can learn from the history of how the organization actually behaves. Aera Technology co-founder and CEO Fred Laluyaux will open AeraHUB with a keynote on the decision-centric enterprise. His argument is that the next stage of enterprise AI should ultimately be measured not by the number or sophistication of models a company deploys, but by the quality and volume of business decisions those systems can improve. For corporate leaders, that changes the AI conversation from model selection toward operating design: which decisions should be automated, which should remain human, and how should the two interact? The Summit will also provide the first look at new Aera capabilities for building, governing and scaling decision intelligence. Governance is likely to become particularly important as enterprise AI moves from advising people to taking actions. An AI assistant producing an imperfect summary is one level of risk; an autonomous system changing inventory allocations, production schedules or purchasing decisions introduces a very different requirement for policies, auditability and control. That transition will be explored further in a session on the autonomous enterprise and the future of work with Harvard Business School professor Joseph Fuller, co-director of the Managing the Future of Work project. The discussion will examine what happens as AI moves from experimentation into the operating model of companies and begins changing not only individual jobs but the allocation of decision-making between people and machines. AeraHUB will also address the more practical problem of getting started. Florian Selch, CEO and co-founder of Masters of Supply Chain, will lead a discussion with representatives from Nufarm, Oncor, So Help Me Understand and Wallenius Wilhelmsen about selecting initial use cases, establishing trust in AI-generated decisions and creating a foundation from which decision intelligence can expand across an organization. Live demonstrations will provide a more concrete view of the autonomous-enterprise concept. Aera plans to demonstrate an autonomous value chain and show how decision architects can design and govern the decisions operating within it. A dedicated product track will cover AI economics, policy-driven decision-making, simulation, teams of AI agents and applications involving forecasting, inventory management and supply-and-demand balancing. The role of the "decision architect" is itself an interesting development. If enterprises increasingly automate decisions, someone has to translate complex business processes into explicit objectives, rules, constraints, exceptions and escalation paths. AeraHUB will include hands-on Decision Architect Training covering how complex decisions can be decomposed, structured into decision frameworks and digitized in the Aera platform. Consulting and implementation firms are also becoming part of this developing ecosystem. EY, Accenture, Deloitte and ZS Associates will present their perspectives on implementing and scaling decision intelligence, an indication that the technology is beginning to develop the broader services layer normally associated with enterprise platforms moving from experimentation toward large deployments. The Summit arrives at a particularly interesting point in the evolution of corporate AI. Generative AI demonstrated that machines could interact with employees through natural language. AI agents are now demonstrating that software can perform sequences of tasks with less human intervention. Decision intelligence takes the next step by applying similar capabilities directly to recurring business decisions. The long-term implication is potentially an enterprise in which thousands or millions of operational decisions are continuously evaluated by software, routine choices are executed automatically and humans concentrate on exceptions, objectives and strategic judgment. That is still an emerging model rather than a completed transformation, and questions around reliability, accountability and governance remain substantial. AeraHUB 26 NYC should provide a useful look at how far that transition has actually progressed inside large companies. With organizations from pharmaceuticals, energy, consumer products, logistics and manufacturing presenting real deployments, the October gathering will offer something more useful than another general discussion about what AI might eventually do: a view of where enterprises are already willing to let AI participate in the decisions that run their businesses. AeraHUB 26 NYC takes place October 27-28, 2026, at Pier Sixty in New York City, with participation available both in person and virtually.

Climate & Decisions, Aera launch climate decision intelligence solution. Mon, 21st Sep 2026 (Today) Climate & Decisions and Aera Technology have launched Climate Decision Intelligence, a product designed to help organisations turn climate and sustainability information into business decisions. The offering combines Climate & Decisions' advisory work in climate risk, governance and operating models with Aera's decision intelligence software platform. It enters a market in which companies are collecting more climate data through emissions reporting, supplier assessments, transition plans and risk analysis, while facing pressure to show how that information shapes day-to-day commercial choices. At launch, the product includes five pre-defined decision tools focused on supply chain resilience, carbon-aware promotion, carbon budget optimisation, supplier risk and sustainable sourcing. The tools are intended to connect climate-related signals with financial and operational context, assess response options, and route recommendations to business owners for approval, modification or escalation. The announcement reflects a wider shift in corporate climate work. Many organisations have built reporting processes for disclosure and compliance but have struggled to connect those exercises to pricing, procurement, logistics, inventory and sourcing decisions that affect revenue, margins and service levels. Climate-related disruption has become a more immediate operational issue for many sectors, particularly in supply chains. Extreme weather events, regulatory shifts and changes in supplier performance can force companies to weigh cost, resilience and emissions trade-offs at short notice. Climate Decision Intelligence is intended to make those trade-offs more explicit. In practice, a climate event affecting a supplier, a breach of an internal carbon budget, or a deterioration in a supplier's sustainability rating could trigger a recommendation within an existing business process. Initial focus The first of the five tools, supply chain resilience, is intended to help companies protect product availability and service levels when climate events disrupt suppliers, transport routes or stock positions. Another, carbon-aware promotion, is designed to identify changes in product mix or campaign planning that reduce emissions while taking margin and availability into account. Carbon budget optimisation focuses on situations in which emissions move outside an agreed budget and recommends adjustments. Supplier risk links sustainability performance to commercial exposure and flags when escalation is needed, while sustainable sourcing compares sourcing options across cost, carbon footprint, service, capacity and risk. Each tool can either generate a recommendation for review by a named business owner or support automated execution where a company permits it. The system also keeps a record of context, actions and outcomes to create an audit trail and a history of earlier decisions. That auditability is likely to matter for companies adapting to more formal climate disclosure standards. Businesses are under increasing pressure to show not only that they can identify climate-related risks and opportunities, but also that governance processes link those issues to strategy and financial performance. The companies pointed specifically to IFRS S2-aligned disclosure requirements as part of the backdrop to the launch. Those rules have raised expectations that climate reporting should connect to board oversight, capital allocation and operational decision-making rather than remain a standalone reporting function. Aera, founded in 2017, has built its business around what is widely referred to as decision intelligence software. Its systems are used to analyse operational data, generate recommendations and automate some choices under defined governance settings. Climate & Decisions, based in Australia, works with boards and management teams on climate disclosure, risk assessment, scenario analysis, transition planning and governance. The partnership gives it a software route for clients that want to embed climate factors in repeatable business decisions rather than address them only through advisory projects. Thierry Lotrian outlined the problem the firms say they are trying to address. "The market does not need another climate dashboard. It needs a faster, more governed path from climate signals to business action. A climate event, carbon-budget deviation or drop in supplier sustainability performance can quickly become a revenue, service, margin and risk decision. Every climate decision is ultimately a business decision, and this solution embeds climate intelligence into the decisions that shape enterprise performance, while keeping judgement, ownership and accountability with the business," said Thierry Lotrian, Chief Executive Officer and Founder, Climate & Decisions. Rajeev Mitroo said the commercial test is whether climate information improves decisions rather than simply adding to reporting workloads. "Organisations have invested significantly in climate data, risk analysis and sustainability reporting, but the real value comes when that intelligence improves a business decision. This is a practical example of agentic decision intelligence helping businesses move from climate ambition to measurable action," said Mitroo. Organisations can begin with a single repeatable use case and configure decision rules, data inputs and approval paths around their own operations, while business owners retain control over recommendations and actions.