Ankur Rimjhim, a senior director at Sify Digital Learning, spends much of her week talking with learning and enablement leaders at large technology companies and at organizations in regulated industries. Their job is to keep learning in step with product releases, regulatory changes, and new platforms. Each of those changes creates training work for learning teams that already have full workloads.
We asked Ankur what L&D leaders have been raising in 2026, how AI is changing the work of their teams, and what teams can do when demand outpaces their capacity.
Here are the top things that have come up for leaders this year.
Learning teams are asked to produce more training, faster
“Content needs to change quickly and at scale,” Ankur says. Product launches, certification updates, and new regulations all require updates to training, and the business sets the deadlines.
Alongside new training, learning teams handle two other kinds of work. They convert older training into formats employees will use, and they update training that’s already live.
Older training can sit in formats that don’t suit how employees learn at work, such as long PDF manuals, slide decks from instructor-led sessions, or hour-long recorded webinars. Ankur described one learning team in a regulated industry that had a collection of recorded webinars employees weren’t watching. “Nobody is going to sit through a one-hour webinar to find some content,” she says. The team wanted to break the webinars into short microlearning modules. It had the tools to do the conversion, but not enough people capacity.
Live training also needs regular updates. When a product changes or a regulation is revised, every course that covers it has to change too. “Companies have realized that maintenance is something you need to deal with up front,” Ankur says.
That maintenance work adds to everything else on the team’s list. The same learning team is usually responsible for three kinds of work: building new training, converting older content, and keeping live courses up to date. With a fixed number of people, whatever the team doesn’t prioritize gets delayed.
AI speeds up drafting – and shifts the work to review
L&D leaders are hearing a lot about AI and asking whether it can help their teams keep up with new training, conversions, and updates.
Ankur sees AI speeding up specific steps in building training, such as drafting a storyboard, the script and screen-by-screen plan for a course. AI tools still depend on people who understand the learners. “Even if I have the best storyboard creation tool, connected to the best data sets, I still need somebody who knows how to write storyboards for the users,” she says.
That dependency changes the instructional designer’s job. “Say an instructional designer used to spend two weeks creating a storyboard. That was the heavy lift. AI drafts it now,” Ankur says. “What becomes more important now is the designer’s judgment. An experienced designer can look at an AI draft and quickly decide what’s useful, what to keep, and what to remove.”
For L&D leaders, this changes how to plan their team’s time in 2026. Drafting takes less time. Review, approval, and updates take more of it, because every AI draft still needs an experienced designer to check it and an SME to sign it off. A team that plans headcount around how long it takes to build content may find that most hurdles are experienced at review and sign-off.
How to tell when your team needs outside capacity
When demand rises, learning teams will often try to cover the additional workload themselves. Instructional designers take on more courses at the same time, and lower-priority training projects get put off. That approach only works for so long. These four situations are common signs that a team needs more capacity:
- A release or event needs more training than your team can build in time.
These are moments of need for large volumes of content. - Useful knowledge is stuck in formats employees don’t use.
Recorded webinars and ILT programs hold knowledge the business needs, in formats that don’t fit how people learn at work. - Review and approval can’t keep up with drafting.
AI drafts and ongoing updates both produce more content for review, and the SMEs who approve it also have other responsibilities. - A new platform needs content before it can launch.
Someone still has to upload content, check it, and approve it.
Annual budget planning is a good time to check for these signs.
Outside capacity works best when it adds to your existing team
When a team has more work than people, the obvious option is to hire. Some teams can’t hire because of a hiring freeze, even when they have budget for projects. Others already have the right skills on the team but can’t produce enough training at a reasonable cost.
Ankur gave one example of the second situation at a Fortune 100 company. The company already had its own in-house video team supporting its certification programs. As those programs needed more video, the team couldn’t keep up at a cost that worked. It made about 10 videos a quarter. With outside capacity from Sify Digital Learning, the company now gets about 40 videos a quarter for a similar cost.
In this model, Sify designers work inside the company’s own AI-assisted process. They write storyboards with the company’s AI tools and keep content up to date across its certification programs. The company keeps its own process and tools, and gets more output from them.
New platforms add work that someone has to staff
Capacity problems also typically show up when a company rolls out a new learning or sales enablement platform. These platforms gather training and sales content from across the company into one place. Before employees can use one, people have to upload the content, check it against brand and quality standards, and approve it. That work continues after launch, as content is added and updated.
“Even when you get a platform in, there’s still the ramp-up that needs to be done,” Ankur says. “After that, content still has to be created, maintained, and approved.”
In one example Ankur described, a global data infrastructure company was rolling out a sales enablement platform. Its sales content was spread across many different teams. The company wanted its sales engineers and partners to find consistent material in one place. Its rollout team had two people and expected up to 500 pieces of content a month, each needing a brand and quality check. It had one quarter to launch.
Sify supported the rollout with a US-based lead and a small team of reviewers who trained alongside the company’s staff. Together they now review content about three times faster than the company’s target turnaround. The company launched the platform within the quarter.
Contract staff and managed projects add people in different ways
When a team needs more people, it can hire contract staff or bring in a partner to run the work as a project. Both add people. The main difference between the two is who manages the work day to day and who looks for ways to improve it.
The data infrastructure company rolling out the sales enablement platform (mentioned above) could have hired contractors to review its content. It chose to run the work as a project with a partner instead. Ankur sees both as reasonable choices that depend on what the team needs.
When an L&D team hires contractors, the team manages each person and is responsible for improving the process. In a managed project, a learning services partner (such as Sify Digital Learning) oversees the work, tracks turnaround and quality, and uses that data to improve the process.
“With a project, there’s governance. We oversee the work and use the data to improve the process,” Ankur says.
A flexible path adds capacity in stages
Bringing in outside capacity raises a practical question for L&D leaders: how much work to hand over, and when. Handing over a whole learning operation at once is a big commitment. Starting with one area of work lets a team see results before deciding what comes next.
A flexible path from need to scale answers that question. Ankur says that path usually has three stages.
- Consulting. An outside view of where the team’s time goes, and which area of work would benefit most from extra capacity.
- Project support. Help with a defined project, such as converting a content library or ramping up a new platform, while the team keeps full control.
- Ongoing operations. Once a type of work is repeatable, such as course updates or platform administration, a partner runs it on the team’s behalf.
Ankur sees most teams move through these stages as the relationship builds. “Start with one priority, add capacity where it helps, then move repeatable work into a managed model where it makes sense,” she says. The first project usually runs around three months, with a clear starting point to measure results against.
Whatever the stage, the learning team stays in charge. “The customer keeps the context, the SME decisions, and the approvals,” Ankur says. “We [at Sify Digital Learning] provide the design, production, and delivery capacity around them.”
Where to start
The best first step is to find where your team is under the most pressure. Ankur frames it as one question: “What is the one learning workflow you need to make materially faster, easier, or more scalable in the next 90 days?”
The answer shows where to start, and it gives the first project a target to measure against.
Two big tech learning leaders on a year of building with AI
Two questions from this blog, where AI really saves time and how much review capacity a team needs, are the focus of a Training Industry webinar on October 28 at 1 p.m. ET. Leaders from two global companies will share what their first year of building with AI has looked like, including which expected savings held up and what instructional designers own now.
Sify Digital Learning provides consulting, professional services, and managed learning operations for global enterprises. Get in touch to talk about the work your team needs to scale first.
