A new study from agentic AI platform Maybe has found that for 61 percent of marketers, AI has increased, instead of simplified, their workloads, FutureWeek reports exclusively.
The report, titled The Big AI Secret, anonymously surveyed 1000 senior marketing professionals to find out their candid, true feelings on AI implementation, development, and where they feel they’re at with their AI initiatives.
The research states that despite marketing and creative agencies being at the forefront of AI adoption, with implementation higher than most other sectors, marketers across the board struggle to realise its promised benefits.
The biggest pain point for marketers is data. From data quality and integration to accessibility – marketers report data issues as the leading barrier to successful AI use.
Other barriers include fragmented processes and tool overload, limited headcount yet growing demand, high volumes of repetitive work, a lack of prompting capabilities, concerns about content authenticity, governance and regulatory uncertainty, and no clear strategy for scaling initiatives.
“When marketers go to LinkedIn, all they see is success stories,” says Polly Barnfield, CEO at Maybe. “There’s so much hidden AI and confusion where people feel they’re falling behind, but there’s a lack of honesty because there’s so much hype. The report is called The Big AI Secret because it’s anonymised and having honest opinions about where people are at with AI is really valuable.”
Workloads Changing, Not Improving
When AI first came onto the scene, the possibility of efficiency and time savings seemed promising to most marketers. However, 61 percent of those surveyed say their workloads have increased since AI initiatives came about – in part, because of the amount of new skills related to AI that are having to be acquired.
Prominent skills gaps, as well as a lack of AI-literate staff in an organisation, increases the need for external consultants and slows the pace of AI integration.
Despite significant uptake of AI across the marketing industry (92 percent) only 8 percent of marketers describe themselves as “fully confident” in their ability to use AI.
An element of this low confidence is grounded in a lack of trust around AI use. The study showed reporting, CRM updates and campaign management as key areas where small AI-related errors produce a disproportionately negative impact on the organisation.
Much of this, according to those surveyed, is grounded in AI hallucinations and the inability of AI tools to admit when they don’t know something.
One respondent said: “Make the AI stop lying. If it doesn’t know, it doesn’t know. We’ll save hundreds of hours in development time.”
76 percent of respondents said they would adopt AI more if it connected directly to outcomes like leads, content performance or ROI tracking. “I was surprised to see in the report the lack of connectivity between AI and the rest of the marketer’s tech stack,” said Barnfield. “It’s not about wanting more output from using an LLM, people want it to fit in their tech stack and be a teammate. It’s the connectivity piece that’s a strategic opportunity here.”
ROI Yet to Be Seen
The study found that the top use cases for AI are content creation, customer insight generation, and campaign planning – however, only 12 percent of marketers are seeing consistent commercial outcomes from these AI efforts.
Return on investments are therefore widely yet to be seen, but this isn’t necessarily down to the AI tools implemented not working as expected.
One respondent said: “Future economies will be shaped by how we conserve and leverage time and energy.”
Rather, marketers feel they aren’t measuring their AI initiatives effectively, with 47 percent admitting they’re not measuring the correct outcomes of their initiatives.
Some issues around measurement include not having a baseline to quantify improvements, attribution challenges, shifting success requirements and intangible benefits like improved creativity and decision making.
Barnfield continues: “Three of the main blockers are scepticism, compliance, and ROI. I would say to any organisation to replace ‘return-on-investment’ with ‘return-on-intelligence’ – how can we use AI to help us make our organisation’s collective intelligence better? The next competitive edge comes from integrating human and synthetic intelligence.”
The Solutions
In response to these challenges, marketers detailed in the report strategies they’ve employed to overcome them. This includes:
- Consolidating AI tools to a single platform – using a single platform, instead of many disparate tools, provides a solution to some of the above issues around governance, security, and fragmented processes.
- Using specialised over general AI tools – using tools specific to existing workflows tends to create more value.
- Having an emphasis on skills development – successful teams develop skills around prompt engineering, AI supervision, and use case development.
- Putting governance first – governance works best when it’s not an afterthought and is intertwined
- Integrating into existing workflows – the most successful AI tools work integrated with existing tools instead of operating independently.
The report is available to download on Maybe’s website, along with an interactive report chatbot that lets users ask questions about the report’s findings through conversational language.
Maybe offers a no-code platform to build outcome-driven AI agents for enterprises.
