Six Keys to Consider Before Implementing AI Agents

Key Points:

• Identify specific tasks and processes where AI agents can make compelling contributions

• Understand and address privacy, security, and ethics vulnerabilities prior to implementation

• Communicate transparently with employees, offer training, and address their concerns

AI agents have been explosively trending this last week. AI agents, as voyAIge strategy’s Co-Founder Dr. Christina Catenacci describes, are applications that use a combination of different AI models together with conventional automation frameworks to process information – without human interaction. The goal of the AI agent is thus to supplement or even supplant human workers.

Unlike the AI many of us have explored in the course of the last calendar year, AI agents have autonomy. They make decisions, perform tasks, and create outputs based on defined goals. With companies like Microsoft and Salesforce introducing AI agents, many organizations are considering incorporating them into their operations, and rather quickly.

However, it is essential to consider precisely what is at stake in adopting AI agents. How will they change workflows? What impact will they have on workforce morale? In what ways do they – and perhaps do they not – align with your organization’s goals and growth plans? Thoughtful, informed preparation is crucial if we are to ensure that AI agents enhance as opposed to impede critical processes.

Here are key considerations that can help generate conversations with your business line leaders and executives that can cultivate the strategic planning and insight your organization requires if/when implementing AI agents – especially if you are considering them in the long term:

Define Objectives, Values, and Use Cases

Before adopting AI agents, pinpoint exactly what value they can provide. A common misconception is that AI agents can immediately replace complex tasks or roles. This is not the case, especially in early stages where human oversight and model adjustment is required. Moreover, different departments and processes will benefit from AI agents in different ways.

Begin by auditing your organization. Identify tasks that are repetitive, rule-based, and time-consuming. These are often prime candidates for automation. Basic administrative tasks, inventory management, calendar scheduling – these are all prime examples of time-consuming tasks that can benefit from an AI agent’s assistance. Start small. Focus on specific workflows and expand from there.

Prioritize Security and Privacy

AI agents process large amounts of data. Some of those data are sensitive. Given that 51% of employees have tried tools like ChatGPT in the last year and only 17% of employers have AI policies that may otherwise regulate what information employees give to AI systems, there is already a risk in your organization whereby employees are feeding to an AI system client information, data measurements, and insights valuable to your brand. Employees are significantly outpacing their employers in using AI at work and this blind-spot can be highly problematic, opening your organization up to non-compliance and legal risks because most AI systems that employees are unofficially using at work train and model from the data anyone provides them. When dealing with AI agents, the potential risk increases quite significantly.

If you do not have AI policies in place as well as data privacy policies, these are crucial requirements. You will also need to develop and  implement a clear data governance policy to ensure that AI agents handle your own and your stakeholders’ data safely and securely.

Establish a Clear Accountability Structure

Because AI agents act autonomously without direct human input, it is difficult to know how their decision-making will align with and deviate from an organization’s values, priorities, and procedures. If and when an AI agent misses the mark, who is accountable for reporting and addressing these errors – and to whom are they accountable, exactly?

Establish ethical guidelines for AI agents before they are fully implemented and deployed. How should an AI agent handle sensitive situations? What exactly defines a sensitive situation as well as sensitive information? When should certain decisions by deferred to a human decision-maker? Layers of oversight that are clearly articulated in AI ethics policies and accountability policies ensuring that AI agents can be audited and adjusted if they make inappropriate or harmful decisions. Create a governance structure that holds specific teams and roles accountable for monitoring and managing an AI agent’s actions.

Assess and Understand Workforce Impact

The introduction of AI agents will change the nature of work in your organization. While it is true that AI agents will likely return valuable time to your hardworking employees, 38% of employees are nervous that AI will replace them while 51% worry that AI will negatively impact their mental health. There is considerable likelihood that your workforce will have questions and concerns.

Engaging employees honestly, accurately, and giving them avenues to be heard is critical if any AI system is to work in an organization. It is recommended that businesses use transparent communication with employees . It is paramount that AI agents are clearly explained, described and situated within specific roles and contexts. Employees need to hear that they will not be replaced. HR leaders are recommended to be proactive in providing training opportunities that help employees adapt to these changes as well. Work should be undertaken to restructure roles to reflect altered workflows.

Start Small with a Pilot Program

Mass implementation of any digital solution is risky. While software and automated tools can save time, they need to be learned before they are fully understood and embraced. A pilot program is a small-scale, isolated, and controlled study that allows an organization to understand feasibility, cost, roadblocks, and opportunities in isolation.

Choose a single team, department, or process for your pilot project. For example, automating customer complaint responses. A controlled approach with a small team testing an AI agent over the course of a couple of months allows you to gather data on the effectiveness of AI while minimizing disruption. Choose a team of individuals that understand and familiar with AI, preferably employees that are excited about AI who can champion the cause and socialize it later. Use the pilot’s findings to make any necessary adjustments.

Develop a Monitoring Plan

AI systems learn. They change by adjusting their behaviour in an attempt to improve over time. Like a teacher in a classroom, how one learns is as important to the learning process itself. Testing, monitoring, and providing opportunities to expand horizons is crucial to any person or AI system’s successful growth. 

To facilitate successful growth, establish a team that will monitor the AI agent’s performance. Regular audits should become a part of your organization’s AI governance repertoire. Establish key performance indicators (KPIs) to measure the AI agent’s success in meeting its goals, adjusting along the way as needed. Continuous monitoring not only helps mitigate risks, but it will ensure successful and smooth operation in the long-term.

Adopt for Long-Term Success, Not Short-Term Gain

As with any release of new technology, industry and media hype tremendously stimulates early adoption. A challenge of early adoption is not being aware of a technology’s limits and challenges. Left unchecked and misunderstood, they can derail investments and disturb workforces. Start small, stay informed, and ensure that both technology and human talent are aligned for future success.