Rather than asking how AI agents can work for them, a key question in enterprise is now: Are agents playing well together? This makes orchestration across multi-agent systems and platforms a critical concern — and a key differentiator. “Agent-to-agent communications is emerging as a really big deal,” <a href="https://www.g2.com/">G2’s</a> chief innovation officer Tim Sanders told VentureBeat. “Because if you don&#x27;t orchestrate it, you get misunderstandings, like people speaking foreign languages to each other. Those misunderstandings reduce the quality of actions and raise the specter of hallucinations, which could be security incidents or data leakage.”<h2>Allowing agents to talk and coordinate</h2>Orchestration to this point has largely been around data, but that’s quickly turning to action. “Conductor-like solutions” are increasingly bringing together agents, robotic process automation (RPA), and data repositories. Sanders likened the progression to that of answer engine optimization, which initially began with monitoring and now creates bespoke content and code. “Orchestration platforms coordinate a variety of different agentic solutions to increase the consistency of outcomes,” he said. Early providers include Salesforce MuleSoft, UiPath Maestro, and IBM Watsonx Orchestrate. These “phase one” software-based observability dashboards help IT leaders see all agentic actions across an enterprise. <h2>The critical element of risk management</h2>But coordination can only add so much value; these platforms will morph into technical risk management tools that provide greater quality control. This could include, for instance, agent assessments, policy recommendation and proactive scoring (such as, how reliable agents are when they call on enterprise tools, or how often they hallucinate and when). Enterprise leaders have become wary of relying on vendors to minimize risks and errors; many IT decision-makers, in fact, do not trust a vendor&#x27;s statements about the reliability of their agents, he said. Third-party tools are beginning to bridge the gap and automate tedious guardrail processes and escalation tickets. Teams are already experiencing “ticket exhaustion” in semi-automated systems, where agents hit guardrails and require human permission to proceed.As an example: The loan process at a bank requires 17 steps for approval, and an agent keeps interrupting human workflows with approval requests when it runs into established guardrails. Third-party orchestration platforms can manage these tickets and nay, yay, or even challenge the need for approval altogether. They can eventually eliminate the need for persistent human-in-the-loop oversight so organizations can experience “true velocity gains” measured not in percentages but in multiples (that is, 3X versus 30%).“Where it goes from there is remote management of the entire agentic process for organizations,” Sanders said. <h2>‘Human-on-the-loop’ versus ‘human-in-the-loop’ </h2>In another critical evolution in the agentic era, human evaluators will become designers, moving from human-in-the-loop to human-on-the-loop, according to Sanders. That is: They will begin designing agents to automate workflows. Agent builder platforms continue to innovate their no-code solutions, Sanders said, meaning nearly anyone can now stand up an agent using natural language. “This will democratize agentic AI, and the super skill will be the ability to express a goal, provide context and envision pitfalls, very similar to a good people manager today.”<h2>What enterprise leaders should be doing now</h2>Agent-first automation stacks “dramatically outperform” hybrid automation stacks in almost every attribute, he noted: satisfaction, quality of actions, security, cost savings.Organizations should begin “expeditious programs” to infuse agents across workflows, especially with highly repetitive work that poses bottlenecks. Likely at first, there will be a strong human-in-the-loop element to ensure quality and promote change management. “Serving as an evaluator will strengthen the understanding of how these systems work,” Sanders said, “and eventually enable all of us to operate upstream in agentic workflows instead of downstream.” IT leaders should take inventory today of all the different elements of their automation stack. Whether these elements are rules-based automation, RPA, or agentic automation, they must learn everything going on in the organization to optimally use emerging orchestration platforms.“If they don&#x27;t, there could actually be dis-synergies across organizations where old school technology and cutting edge technology clash at the point of delivery, oftentimes customer-facing,” Sanders said. “You can&#x27;t orchestrate what you can&#x27;t see clearly.”

إن دمج وكلاء الذكاء الاصطناعي في البيئات المؤسسية يغير التركيز من قدرات الوكلاء الفردية إلى قدرتهم على التعاون بشكل فعال. يؤكد تيم ساندرز، كبير مسؤولي الابتكار في G2، على أهمية التنسيق في أنظمة الوكلاء المتعددة لمنع سوء الفهم الذي قد ينشأ عن التواصل الضعيف، مما قد يؤدي إلى مخاطر أمنية أو تسرب بيانات.

La integración de agentes de IA en entornos empresariales está cambiando el enfoque de las capacidades individuales de los agentes a su capacidad para colaborar de manera efectiva. Tim Sanders, director de innovación de G2, enfatiza la importancia de la orquestación en sistemas multi-agente para prevenir malentendidos que pueden surgir de una comunicación deficiente, lo que puede llevar a riesgos de seguridad o filtraciones de datos.

L'intégration des agents IA dans les entreprises déplace l'accent des capacités individuelles des agents vers leur capacité à collaborer efficacement. Tim Sanders, directeur de l'innovation chez G2, souligne l'importance de l'orchestration dans les systèmes multi-agents pour éviter les malentendus qui peuvent survenir en raison d'une mauvaise communication, ce qui peut entraîner des risques de sécurité ou des fuites de données.

The integration of AI agents in enterprise settings is shifting focus from individual agent capabilities to their ability to collaborate effectively. Tim Sanders, chief innovation officer at G2, emphasizes the importance of orchestration in multi-agent systems to prevent misunderstandings that can arise from poor communication, which may lead to security risks or data leakage.

AI agents can talk — orchestration is what makes them work together

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AI agents can talk — orchestration is what makes them work together

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