It should come as a surprise to approximately no one that AI is already playing a role in automating and optimising customer advocacy programs. While maturity across the industry varies, it’s clear that the push is towards greater integration, automation, and enhanced customer experience.

Where is AI in customer advocacy heading? The key is not treating AI as a one-off tool but embedding it into the core of operations across the entire customer advocacy lifecycle. Moving beyond simple automation to create an AI-accelerated program which optimises budgets saves time and allows teams to scale programs more efficiently.

Let’s look at how programs might put this into practice.

Optimising the advocacy workflow

• Recruitment: AI can leverage advanced analytics to identify potential advocates and tailor engagement strategies based on preferences. Gen AI tools can also be used to draft personalised recruitment emails for customers and sales teams, ensuring outreach is both efficient and tailored. Furthermore, automation (such as structuring data for Zapier) can cut hours of manual work related to advocacy recruitment at scale.
• Engagement: For high-impact programs, AI could be utilised to actively track the customer journey and build a fully personalised advocacy experience throughout.
• Discovery and research: Before engaging a customer, teams can leverage deep research, which AI will summarise to facilitate more insightful and strategic discovery conversations. This ensures content aligns precisely with every customer’s interests.
• Metrics and reporting: AI is poised to impact the delivery and tracking of metrics reporting, removing the need for manual processing. AI tools can be used to analyse reference tracking data, allowing teams to quickly query and generate reports on program health, for example.

Accelerating content creation and activation

• Story capture: During customer calls (such as in Google Meet), Gen AI can automatically generate transcripts and ‘take notes for me’ summaries. These summaries can then be fed into custom AI tools to create a high-level overview of the story.
• Editorial efficiency: At the beginning of the story process, background information can be ingested by AI and utilised to create highly targeted interview guides. For written content, feeding a transcript into a custom AI tool can generate a high-quality first draft, reducing the time required for a final editorial review. Similarly, for video, AI can analyse transcripts to help teams quickly pull-out key soundbites for video paper edits and storyboards.
• Activation and knowledge management: AI will quickly become instrumental in accelerating the distribution of stories. AI tools can craft social media copy for content amplification and create pre-formatted slides for sales enablement, thereby accelerating the sales cycle. For managing internal knowledge, a dedicated AI instance can be pre-loaded with all public customer assets, acting as a personalised AI expert that internal stakeholders can query using natural language.

The boundary: where AI stops and humans prevail

This should be an obvious point to most, but the core mission of advocacy remains fundamentally human. Advocacy is built on relationships, relevance, and ensuring the right story is told at the right time. Authentic voices (including your own!) are essential for maintaining consumer trust.

AI’s role is to amplify human connection, not replace it. By automating repetitive tasks, AI will free up customer marketing and advocacy professionals to dedicate their time to fostering stronger customer relationships and engaging in higher-level creative work. The establishment and growth of essential relationships remain solely the domain of human practitioners.