A look at the pros and cons through the 4-step content development process.
After a stimulating networking event with the Greater Manchester Chamber of Commerce, where we were treated to an insightful live demo of Microsoft’s Co-Pilot AI platform, it got me thinking about the pros and cons of AI in content marketing, especially when it relates to the production process.
AI continues to divide opinion when it comes to end-to-end content marketing strategies and execution. On the one hand, it has levelled the playing field and created massive efficiencies for brands struggling to find resources and budgets. However, it has also exacerbated some of the age-old issues the industry has always faced, namely increasing the volume of bland, generic and uninspiring content that should be sent straight to the landfill.
AI has massive benefits for creative content production, but let’s review the basic 4-step process for content planning and production and see where it is actually benefiting and where it is hindering the process.
For the purposes of this blog, I have simplified the process into 4 stages:
- Strategy and planning
- Content production
- Approval process
- Publication and distribution
B2B content marketing can prove complicated as topics tend to be complex and technical in nature, requiring greater research, expertise and, in many cases, regulatory approval. The end-to-end process can be incredibly long and painful if not managed correctly.
The problem is that for B2B marketing, the end-to-end process can only move at the speed of the slowest stage. If AI dramatically reduces the time and resources required for some but not all stages, a bottleneck will inevitably be formed.
Stage 1 – Strategy and planning
There are considerable benefits to having AI in this process, massively cutting the time and increasing the scale of overall content strategies, including audits, competitor reviews and content calendars. Using AI to speed up the time-consuming groundwork frees the real brains to focus on creating a meaningful, emotion-backed strategy.
Stage 2 – Creative content production
Here, there are split benefits. There are time benefits of using AI for the first stage of content planning, i.e. synopsis creation for scripts, articles and whitepapers. However, achieving the technical nuances, finesse, and subtlety required to create emotional content requires thought-provoking specialist knowledge and input from real people.
Stage 3 – Approval process
Here lies the major problem. If the first two stages benefit from AI in the speed of production, inevitably, more content will be produced. Many B2B brands were already struggling with content approval due to several factors, including multiple stakeholders, regulation and legal, and senior stakeholders only getting involved late in the process.
By way of an example, we worked for a major consultancy firm a few years back, creating a multi-platform content series to support their original research projects. Issues arose because whilst it took 1-2 months to develop the content it took a further 2-3 months to get final regulatory and senior management approval. By the time the content was finally published, it, unfortunately, felt dated.
Stage 4 – Distribution and amplification
Here is where AI comes into its own. There are massive benefits to creating multiple social posts, paid posts, and personalisation assets to promote the content piece/campaign. In turn, AI assistance in wading through the masses of data into actionable insights is invaluable. However, how this gets interpreted and applied to something meaningful will always rely on real-life experience.
At The Point Consult, we are huge fans of AI and believe that used in tandem with experienced real-life humans can positively affect the B2B content ecosystem. However, the content production process and the internal brand approval processes must be aligned and agreed upon before any project kick-offs; that way any potential bottlenecks can be ironed out, and expectations can be aligned.