AI and advanced automation techniques have transitioned from being a future prospect to becoming central to the operations of many B2B enterprises. With more advanced automation techniques available daily, recent Algomarketing global research highlights a consistent barrier to accessing this level of advanced automation, the AI and automation skills gap.
Skills Gap is a Challenge to AI Adoption
Almost half (44.4%) of global marketing leaders see the skills gap as a challenge to AI adoption.
Any large B2B enterprise is struggling with the need to attract specialist AI and advanced automation talent while evolving their existing team capabilities and considering the best team structure to deploy the technology effectively.
The talent situation is complex, involving identifying talent with core AI and ML skills, cultivating blended skills that combine data science with business knowledge, and building a wider data-literate workforce.
Digital Upskilling for Next Generation of Employees
Many forward-thinking global brands have started to introduce AI literacy and digital upskilling to help prepare for this transformation, with university partnerships becoming more common.
But with only 23.2% of major companies having adequate internal resources for AI, a blended trend is emerging in overcoming the AI skills gap, combining in-house teams with 3rd party expertise.
“Large-scale global businesses have the challenge of deploying AI and automation at scale, typically without in-house expertise to guide this type of operation at speed. Just 12 or 18 months ago, the only way to do this was to access advanced AI or ML expertise through data scientists and analysts. But recruitment is both time-consuming and expensive, often requiring a significant sign-off process. Here at Algomarketing, we provide access to those skills and expertise in just days as opposed to weeks or months, helping teams build a strong business case for increased investment to scale the technology through small incremental experiments. We are committed to capturing the in-house human wisdom that is critical in ensuring ethical, quality output as the AI and ML are trained to work as part of the teams we’re helping” - Yomi Tejumola, Founder & CEO, Algomarketing
Introducing a blended AI deployment strategy
Working with established managed service providers (MSP), global businesses are benefiting from contractors joining a client-led team to work within an AI deployment project.
Algomarketing supported a tier one global tech business to design and deliver a 12-week build and deploy pilot model, which supported in-house business case creation for wider roll out, while upskilling existing team members.
These pilot projects can provide evidence KPIs such as:
- Viability: increase in adoption rate
- Self-serve: a decrease in requests to the analytics team as a result of growing in-house capability in accessing and interpreting data
- Colleague satisfaction: satisfaction rate and user experience rates increase
- Time saved: increased productivity as insights are gathered in real time
With demand for data science skills and expertise at its peak, many B2B enterprise brands are recognizing the value of bringing required skills into businesses via managed service provider models. A trend likely to continue to grow as the benefits of immediate access to sought-after skills, while building in-house capability are felt across the bottom line.
Yomi Tejumola, a visionary tech entrepreneur, founded Algomarketing in 2017 to revolutionize marketing through algorithms, drawing from his experience at Google to supply skilled marketing talent globally, and now operates in 27 countries, enhancing big tech brand marketing operations with advanced insights and efficiency.
