It’s easy to improve individual productivity with AI tools. Using an LLM to summarize meetings, draft emails, or search the company’s documents is important and helpful. But what leaders are really seeking is for AI to deliver ongoing business value through agentic workflows and differentiating capabilities.
I’ve been telling C-level leaders that AI is reshaping business in many organizations, but it’s not transforming them yet. To accelerate AI’s path to value, leaders must re-engineer workflows, connect field and back-office operations, and develop customer- and client-facing AI capabilities.
The key shift in many organizations requires developing AI literacy and competencies that everyday employees can adopt – not just the experts and super users. What works for early adopters has given many organizations initial productivity boosts, but acceleration means getting more people excited to partner with AI capabilities and developing new ways of working.
Leaders must seek three building blocks – platforms, partners, and learning programs – that deliver broad AI capabilities all employees can learn and adopt easily. Let me share specifics on how these building blocks help employees move beyond today’s workflows into the future of agentic AI.
Select platforms that empower employees
Many AI solution providers target the most technical employees at large enterprises. These include AI agents embedded in enterprise SaaS platforms and vibe coding tools for advanced software developers.
But how can leaders at industrial SMBs provide AI capabilities to their operational leaders? For example, the construction ops manager conducting a site risk assessment, the project manager doing the weekly capacity plan, or the field ops manager at an HVAC services company optimizing real-time scheduling?
These are examples of dynamic work, where managers must adapt processes to the job’s regular demands and changing conditions. The best people to design these workflows are the frontline managers, and not by hodgepodging spreadsheets, manually integrating a sprawl of SaaS applications, or getting by with other workflow productivity killers.
Leaders accelerate AI’s path to value by empowering the people closest to the work to use AI tools to re-engineer operations. These include AI tools that convert spreadsheets to apps, empower citizen developers with vibe no-code tools, and enable more employees to become smart builders.
Find partners that get you started quickly with best practices
I work with many SMBs looking to modernize workflows and develop AI capabilities. To get the most out of any technology used in strategic operations, I encourage them to take advantage of the solution provider’s extended partnering services and solution marketplace.
Partners bring the expertise to configure AI controls, establish application lifecycle management practices, and configure role-based access controls. These capabilities help the organization manage apps, data, and AI responsibly, without the CIO perceiving citizen development as a shadow IT effort.
Solution marketplaces help operational managers find starter applications that are configurable and extendable. Examples include prefab tracking in construction, shop floor management in manufacturing, and order management for small businesses.
Scale adoption with AI learning programs
To drive transformation, leaders should work with partners on continuous adoption programs that include collaborative and rapid app development. These programs differ from old-school outsourcing projects by enabling co-creation with employees and encouraging employee-led support of deployed applications.
So, while partners accelerate best practices, the organization’s leaders still need to invest in employee development. For this reason, I always review a solution provider’s documentation, learning programs, certifications, and community activities to gauge the resources available to train employees.
Here’s a good example of what to look for when reviewing a solution provider’s offerings.
- Free trials that meet the no-code test of helping a motivated citizen developer build a prototype in their first sitting.
- Documentation should include a starter guide for beginners, a knowledge base of best practices organized by use case, and API documentation for advanced developers.
- A university of learning programs and certifications that enable employees to become expert builders, end users, system administrators, and workflow managers.
- A community program that connects employees with experts and others learning to use the platform.
How platforms, partners, and learning scale AI adoption
You might ask how these three elements—citizen development + partners + learning—scale AI adoption.
AI-enabled workflows connect people and AI agents in intent-based workflows. Instead of prescribing every step, decision, and exception in a workflow, AI agents complete tasks and recommend decisions based on information stored in a context layer.
To scale adoption, leaders need more subject matter experts to re-engineer workflows and build the organization’s context layer. Partners help accelerate this process. Leveraging a solution provider’s smart, easy-to-use learning programs sets an example for the organization’s knowledge management programs. When employees are led by example, they embrace change.
AI is reshaping business, and leaders can accelerate their transformation by re-engineering to AI-enabled, dynamic work management.
This article is brought to you by Quickbase.
The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Quickbase.
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