Here are two broad ways to allow non-IT/engineering employees to gain relevant AI literacy in order to close an unneeded gap…
Traditionally, the focus of AI expertise has been confined to departments such as Engineering or Product Development. However, this approach can limit organizations from fully harnessing the power of AI.
To tap the potential of AI to increase staff productivity and problem-solving skills, Asian businesses can leverage a two-pronged strategy: cultivating AI literacy and skills across departments; and organizing events to foster cross-team collaboration and spark new use cases for AI innovations.
There are now platforms and tools that empower non-engineering individuals across all departments to tap into the potential of AI, regardless of professional background. These resources can be easily integrated into workflows to streamline tasks and boost productivity, yet many non-technical professionals remain unaware of how to leverage AI or optimize their work processes fully or even partially.
Cultivating general AI literacy
It is paramount for competitiveness that organizations initiate internal training programs and workshops to raise AI awareness and cultivate AI literacy, so as to empower employees to confidently adopt and apply AI within their roles.
Businesses can unlock their full potential by equipping both tech and non-tech employees with the level of AI literacy they need.
The precise steps to do this remain a work in progress for most firms, but here is how we did it at Gogolook:
- We embarked on a company-wide deep learning training program to equip our workforce — engineers and non-engineers alike, from business development, design, marketing, and administration teams — to equip them with the foundational knowledge and skills behind deep learning algorithms and useful automation tools.
- The coursework was customized for engineers and for non-engineers: one was based on understanding and using programming tools; the other was based on using platforms that support automation and prompt control of LLMs. Both teams were then invited to collaborate to build fully functional prototypes during an internal company-wide technology event.
- The idea was that the non-engineers would prove usability while the engineers would prove efficiency and scalability.
- For the technical content, we covered the essential math, and topics from simple to multi-layer neural networks, training strategies, to various advanced architectures such as transformers and object detection. Trainees were required to submit two assignments, one with Kaggle and another at the company wide tech event. The whole duration was 12 weeks, 2 hours per session. The most satisfying feedback was that the engineers felt confident they could apply what was learned in their individual product teams and will continue the learning journey.
- For the non-engineers, staff such as UI/UX designers and marketing specialists learned AI-powered semantic analysis and used their new skills to save valuable time and resources, and improve content creation efficiency and quality.
- Overall, the approach fostered departmental ownership of AI. Employees of diverse functions can now explore new possibilities with AI, leading to a more tangible and rapid enhancement of businesses’ overall AI capabilities.
Fostering cross-team collaboration
While nurturing AI literacy across the company is crucial, true innovation often sparks from knowledge sharing and cross-departmental collaboration. Building successful cross-team collaborations for an AI culture demands a specific mindset shift.
Our approach involved initiating internal hackathons and competitions to spark creative thinking across departments. These activities brought together team members from diverse backgrounds to come up with innovative AI-driven solutions. We saw a significant difference between competitions held before and after our internal AI training and workshops. Employees without deep engineering expertise could now leverage their AI knowledge and be able to bring ideas to life.
Employees will have new skills to bring their ideas to life, and spark of innovativeness elicited through brainstorming across teams and departments — potentially leading to applications in existing or future products and services.
By fostering knowledge sharing and cross-departmental collaboration, businesses can spark a cascade of ideas, enhance efficiency, improve workflows, and develop groundbreaking product innovations, paving the way for transformative changes.
Democratizing AI in the office
AI can unleash untapped potential by automating repetitive tasks, freeing up employees for higher-level strategic thinking, and encouraging creative problem-solving.
When every department understands AI’s capabilities, a wellspring of innovative ideas emerges.
It is time to empower your workforce with AI by invest in training across departments, identifying AI opportunities within workflow processes, and fostering a collaborative spirit. In this way, businesses can redefine the future of work and achieve a smoother, more impactful digital transformation.
