Who Controls Intelligent Assistant Decisions in Enterprise Marketing?

The marketing team uses an Intelligent Assistant in their campaign. It takes weeks for the intelligent assistant to suggest actions based on data. The outcomes seem to be very encouraging; however, one thing still remains to be determined: Who will be responsible for that decision?  

For enterprises, it is a matter of determining when assistants can make decisions on their own, when human intervention is needed, and who bears responsibility for the decision made.

The significance of enterprise AI governance is explained in this article.

The marketing team uses the Intelligent Assistant in choosing channels for their campaigns or allocating media budget. However, what if the Intelligent Assistant tends towards favoring its vendor’s own advertisement infrastructure over other competing systems? 

It is essential to differentiate between the optimization of the decision-making and recommendations based on the priorities of a platform. This contradiction has to be managed in Enterprise AI Governance through setting evaluation metrics, providing recommendations transparency, and allowing marketers to challenge the decisions made. 

1. Know Why the Recommendations Are Made

Human evaluator be able to comprehend the logic behind the recommendations made by the intelligent assistant. 

Before taking any recommendations, the marketing manager makes sure there is sufficient evidence from previous data, not just good results.  

2. Incorporate Intervention Points into the Workflow

Human Intervention should be made part of the decision-making process and not come after the action has been done.  

The assistant can find inactive leads and start a re-engagement program. Before executing such campaign, human approval is necessary.    

3. Make Accountability Explicit 

Enterprise AI Governance will identify the people who have to be accountable for the decision-making processes of Intelligent Marketing Assistants. 

Lead scoring falls on the shoulders of the demand generation team while marketing operations are accountable for the performance.

4. Use Exceptions to Highlight Deviation 

The review process should be structured to highlight the exceptions and not the process of going through each action by the team.   

If the assistant consistently requests more budgeting on a particular channel but does not increase the pipeline, then it is flagged and not optimized further.  

5. Evaluate Review Rules with Increased Autonomy

Increase in autonomy entails an analysis of access, authorization, and oversight. 

Approval is required for any change in campaign budget by the team. Once the assistant’s performance is determined, minor changes will be allowed with approval still necessary for larger shifts in budgeting.   

Building Intelligent Marketing Governance  

1. Define Ownership within Teams 

The marketing operations, IT, legal, and compliance need to know about their roles. 

Marketing operations manage access to the campaign, data team manages the audience data, whereas the legal team checks the privacy requirements for personalization.  

2. Make Decision-making Traceable 

Companies have to keep a record of what was advised by the Intelligent Assistant, data used for making the decision, and what action was taken. 

In case an assistant reduces budget on a campaign that performs very well, marketing must be able to see the reasoning for this move.   

3. Analyze Decisions in Terms of Organizational Objectives

The governance framework should be measured in terms of the impact that it has on the organization’s pipeline, conversion, and ROI. 

An assistant that which generates more leads at a lower cost but does not convert them to SQLs, as compared to one which generates more leads.  

4. Limit Access and Vendor Control 

Companies need to limit access to what is needed by the assistant and determine if there is any control or incentive by the vendor to drive their recommendations. 

A paid media optimization assistant does not require access to any customer records. Its recommendations should also be evaluated against comparable channels.   

The real test of Intelligent Marketing Assistants is whether enterprises can turn the decisions into a business advantage. The companies that get this right will be those that know when to trust an Intelligent Assistant and when to intervene.