The arrival of ChatGPT in late 2022 was a watershed moment, capturing the public’s imagination about the potential of generative AI. However, the true power of this technology is only now beginning to be unlocked as businesses move beyond one-off personal use cases and embrace the transformative potential of AI agents.
Our recent poll of business leaders across diverse sectors found that while individual use of consumer-focused chatbots like ChatGPT is common (29%), a growing number of organizations are taking a more strategic approach. Thirty percent are leveraging enterprise-grade AI assistants like Microsoft Copilot, while 10% have even deployed the more advanced Enterprise ChatGPT solution.
This signals a critical shift. AI agents represent a fundamental leap forward from traditional chatbots, capable of autonomously executing complex, multi-step workflows – from data analysis to content creation to task automation.
They offer the potential for far greater business impact than siloed, personal productivity gains. AI agents are more powerful and versatile than any version of ChatGPT. AI-savvy businesses owe it to themselves to consider how this technology resource can yield big operational dividends.
What AI agents are doing for businesses
AI agent frameworks will make it easier to simplify and optimize all sorts of operational functionality throughout the enterprise, whatever the industry.
In a live webinar we hosted, 50% of webinar participants saw AI agents as being helpful everywhere in their organization, reflecting a growing recognition of their wide-ranging applicability. Specific use cases highlighted by participants include complex task automation, improving customer interactions, and enhancing data extraction and analysis capabilities.
AI agents are more powerful and versatile than any version of ChatGPT.
Consider this industry example. An insurance company uses an AI agent to process an email chain and attachments regarding a claim. The AI agent can extract information from the email, including the image showing accident damage, and data from various reports and automatically add it to the company’s claim system, avoiding the need to manually add data. At the same time, it activates an insurance claims AI agent to create a timeline of communications from the email.
Pivot to an industry like energy and utilities, and the same kind of thing can happen: AI agents can research energy consumption trends, rate and regulation filings, or even customer feedback, and then produce reports referencing that information – perhaps a custom report for customers, or one detailing energy savings, a regulatory or compliance document, or promotional materials. These are just the tip of the iceberg, as AI agents can be trained and deployed across virtually any business function.
Possibilities with multiagent frameworks
AI agentic workflows have evolved beyond traditional standalone AI models and chatbots, functioning as an interconnected system of AI agents that work together to accomplish complex tasks and workflows. Unlike standalone AI solutions or single agents, these workflows create a coordinated framework where multiple AI agents collaborate, share information, and complement each other’s capabilities.
For example, in an automated customer service system, one AI agent sorts incoming questions, another finds the right answers in a database, while a third crafts these answers into natural, helpful responses for customers.
The key distinction lies in their ability to operate as a cohesive unit, adapting to changing conditions and leveraging collective learning experiences to enhance performance.
The key distinction lies in their ability to operate as a cohesive unit, adapting to changing conditions and leveraging collective learning experiences to enhance performance. This approach enables the handling of complex tasks that would be beyond the scope of any single AI agent, effectively creating a more robust and versatile AI architecture.
Prepare your organization to deploy AI agents
Organizations can implement and realize ROI with agents if they’re well-prepared to use them. In assessing how ready your business is to deploy AI agents, make sure you have the right technology support for AI and the right governance and security in place around data quality, privacy, and access. Then figure out your potential AI agent use cases — sequence and map them out and determine how to pilot them. Go from proof of concept to pilot and then to a scaled rollout.
For each use case:
- Define specific success KPIs.
- Build the agent with a framework that includes instructions, goals, tools, and human-led quality control.
- Deploy the agent into your workflow.
- Train your staff if a human interface is involved.
- Integrate the agent into your tech stack.
- Scale it to a pilot phase, where you track outcomes and accuracy.
- Scale and roll it out to the whole organization.
Why AI agents fail
Realizing the full potential of AI agents requires overcoming common challenges. Issues around data privacy, security, and regulatory compliance must be navigated. And organizations must develop the right framework to pilot, scale, and measure the impact of their AI agent initiatives.
Even with advanced planning and preparation, AI agents can fail if certain pitfalls are not avoided. The top reasons behind AI agent failure include unrealistic expectations and incorrect usage.
First, people often think AI agents will be right 100% of the time, but that’s not the real world. Organizations need to be clear about the realistic capabilities and limitations of their AI agents, and ensure they always live up to that defined standard of effectiveness.
Incorrect usage is another common issue. This happens when people assign an AI agent a general task with poorly defined guidelines — and they get a suboptimal result with their workflow. Providing detailed, specific, and pertinent instructions and tools are critical to enable the AI agent to perform its tasks.
Unlock competitive advantages
Businesses that get this right can unlock significant competitive advantages. By automating high-volume, repetitive tasks and empowering employees with intelligent agentic frameworks, organizations can dramatically boost productivity, reduce operational costs, and free up human talent to focus on more strategic, creative work.
The age of the AI agent is upon us. Forward-thinking business leaders who move quickly to integrate these powerful tools into their operations will be best positioned to thrive in the years ahead.
Be First to Comment