By Renato Cudicio, MBA – President of TechNuCom
In many Quebec and Canadian SMEs, the same question comes up at every management committee meeting: “Who will take up the torch when our experts retire?” The aging workforce is no longer a distant prospect: it is already impacting the ability to recruit, train, and pass on tacit knowledge. The good news is that AI, automation, and RPA can absorb some of the shock while giving teams some breathing room.
The facts, backed up by figures
According to Statistics Canada, in twenty years, the proportion of people aged 55 and over in the Canadian workforce has risen from 12.6% to 21.6% (2000→2023). In other words, the “pool” of experienced workers is aging rapidly, and their departure is automatically creating skills gaps.
This trend is set to continue: the last cohort of baby boomers will reach age 65 in 2030, and overall labor force participation recently hit a 20-year low (2021–2023).
On the business side, at the end of 2024, nearly two in five companies were already anticipating short-term labor challenges (retention, recruitment, skills shortages).
In Quebec, according to the ISQ, demographic projections confirm the trend: the age structure will continue to shift upward, increasing pressure on the next generation and scarce skills.
It should be added that while some workers are extending their working lives beyond age 65, this postponement is only temporary: the wave of departures and the loss of knowledge are inevitable.
A greater risk than labor shortages: the loss of organizational knowledge
The loss of organizational knowledge often manifests itself in subtle but cumulative ways: experienced employees who retire take with them not only explicit skills (procedures, data, written operating procedures), but also tacit knowledge—work habits, “tricks of the trade,” judgments about what works or doesn’t work in a given situation, and relationships with certain customers or partners.
This tacit knowledge is rarely documented, as it develops over time through daily experience. When it is not passed on, the company may begin to see inefficiencies: mistakes that could not be avoided, repetition of problems that had already been solved, loss of productivity, longer response times to rare or complex situations.
It is difficult to pass on this knowledge.
Passing on this knowledge to young people or those with less experience presents several challenges.
Firstly, tacit knowledge is difficult to formalize: it consists of intuitions, those “invisible” shortcuts that cannot be explained because they have been acquired through habit.
Second, there is often a generational gap in work habits as well as in communication and learning styles—someone who is used to “doing” rather than “documenting” may find it difficult to adopt codification practices or explain what they do naturally.
Third, young people without experience need not only to know “what to do,” but also the “why” behind the company’s decisions, which requires time and mentors, job shadowing, and a certain level of progressive autonomy to experiment.
What is the impact on SMEs?
For SMEs, the impact is often greater, as they have less room for maneuver in terms of resources to compensate for knowledge loss. A typical SME may not have training or documentation services as robust as those of large companies, nor the budget for specialized knowledge management tools.
The departure of a few experienced employees can therefore quickly lead to operational shortfalls: delays, lower quality, and loss of customers if responses or interventions require expertise that is no longer available. In the long term, this can become a competitive disadvantage: less innovation, higher costs for recruiting or retraining, more errors, and sometimes difficulty maintaining continuity when one of the company’s “memories” leaves.
AI + Automation + RPA to the rescue
This is where the combination of AI, automation, and RPA can play a crucial role in limiting or compensating for the “knowledge drain” associated with the departure of baby boomers and ensuring or increasing the organization’s productivity. Here’s how.
# 1. AI: capturing and transmitting tacit knowledge
• Analysis and structuring: AI tools (LLM – Natural Language Processing and NLP – Large Language Model) can analyze internal documents, emails, and procedures, extracting and organizing information in the form of FAQs, guides, or virtual assistants.
• Internal chatbots (RAG): thanks to retrieval-augmented generation, employees can consult an assistant that draws directly on the company’s documentation and history, even after experts have left.
• Intergenerational transfer: AI can serve as an “augmented memory”: it learns from archives and restores knowledge in simple language to new entrants, reducing learning time.
Concrete example: a technician retires; his documented experience is indexed in a vector database (e.g., Pinecone or Weaviate), and an AI assistant can respond to a young employee: “What should I do if machine X displays error Y?”
# 2. Automation: securing and systematizing processes
• Automated documentation: automatic recording of procedures (screenshots, logs, task sequences) to create guides.
• Standardization: automation forces the clarification of implicit knowledge → when a process is automated, it must be described and codified, making it more transferable.
• Error reduction: young recruits do not have to learn everything by trial and error; certain critical processes are automated, limiting dependence on tacit experience.
Example: a customer onboarding flow that previously depended on a senior sales representative is automated via a workflow (e.g., n8n and Power Automate), ensuring that no steps are overlooked.
# 3. RPA (Robotic Process Automation): executing repetitive tasks
• Reproduction of routine tasks: software robots can “imitate” what experienced employees used to do (copy-paste, data entry, data extraction).
• Business continuity: even without a perfect transfer, robots continue to perform repetitive and structured tasks while waiting for new employees to take over.
• Generational bridge: RPA allows young people to focus on high value-added tasks, leaving robots to perform the repetitive tasks inherited from senior practices.
Example: a senior employee manually validated and filed invoices received by email → an RPA-type robot can reproduce this process, avoiding an immediate loss of administrative know-how.
Benefits for SMEs
Thanks to SaaS (Software as a Service) and now RaaS (Robot as a Service) solutions such as those offered by TechNuCom, it is now possible for SMEs to start with simple projects requiring minimal investment and offering a quick return on investment.
Ultimately, some companies will have to take the leap and use an ERP to better structure their data and processes, but the majority can quickly achieve several objectives that directly influence productivity and, therefore, profitability:
• Preserve organizational knowledge: AI + Automation = documentation + accessibility.
• Reducing dependence on certain employees: RPA secures basic operations.
• Accelerating skills development: new employees can rely on AI assistants and already codified processes.
• Increasing resilience: thanks to these technologies, the company is not paralyzed by the sudden departure of an expert.
By relying on the trio of AI, automation, and RPA, it is possible to defuse the time bomb that is the retirement of hundreds of thousands of baby boomers. It is up to us to work together to implement a winning strategy.
