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Techaisle Analyst Insights

Trusted research and strategic insight decoding SMBs, the Midmarket, and the Partner Ecosystem.
Anurag Agrawal

SMB and Midmarket Firms Are Buying More Meeting-Room Hardware as They Grow, Not Less

Hardware spend rises as companies scale, which runs against the assumption that software absorbs everything. Techaisle's study of 3,980 organizations shows where the laptop-and-dongle room breaks, what replaces it, and why the equipment is no longer there to show a meeting but to record one.

Almost every company starts the same way. A screen, a dongle, and whoever's laptop is in the room. It costs nothing, and it works well enough, which is why nobody ever decided to do it. Then, somewhere between the fifth room and the fiftieth, companies stop, and in Techaisle's survey of 3,980 organizations, the switch shows up in spending. USB add-ons for the laptop-and-dongle room fall to 18% at the top of the midmarket, the lowest priority on the whole list, while AI cameras, ceiling microphones, and sensors climb fast. The question worth answering is what they buy instead, and what forced the switch.

What the midmarket is actually buying

All-in-one video bars lead at every size, from 42% in the smallest firms to 56% in the largest, because they work the moment you switch them on. That part is expected. The next tier of spending is less so. AI cameras that follow the speaker rise from 21% to 43%. Ceiling microphone arrays climb from 12% to 37%. Sensors that count people and track how a room is used go from 8% to 31%.

Techaisle chart showing meeting room device priorities rising with company size: AI cameras from 21% to 43%, ceiling microphone arrays from 12% to 37%, and occupancy sensors from 8% to 31%, while USB add-ons for laptop-and-dongle rooms sit last at 18%.

Anurag Agrawal

SMB and Midmarket Contact Centers Keep Losing Their Agents. AI's Real Job Is to Fix That.

Attrition, not missing features, is the contact center's real problem. Techaisle's study of 3,980 organizations shows the fix is a governed AI workforce. The surprise: the most tightly controlled companies give their AI agents the most freedom.

Ask a contact center manager what their hardest operational problem is, and the answer is rarely a software gap. It is that agents keep quitting. In Techaisle's data, attrition is the single biggest challenge contact centers report. The cost of running the operation, the thing most vendors pitch against, actually fades as a worry as companies grow, from 47% of firms citing it down to 16%. The contact center looks like a technology problem. It is a staffing problem wearing a technology budget.

Techaisle chart showing how AI agent autonomy in SMB and midmarket contact centers changes with company size: bounded autonomy pilots rise from 12% to 26%, unattended CRM updates rise from 27% to 42%, and the requirement for human approval of every action falls from 25% to 6%.

The workforce is getting harder to manage

The contact center is the fastest-growing part of the communications market. Agents rise from 4% of the workforce in the smallest firms to 14% in the largest; about 70% of midmarket companies run more than 100 agents, and the real budgets appear in the 100-to-999-employee range.

The work is not going away. Inbound phone calls stay near-universal, at 90% to 95%, so the call is still the core of the job. What changes is where the people sit. More agents work from the office again, up from 43% to 58%, and more work is handed to outside firms, with outsourcing rising from 12% to 33% and offshore staffing from 8% to 30%. A midmarket contact center is now running a workforce that is bigger, more scattered, more outsourced, and still walking out the door. A longer feature list fixes none of that.

The fixes that help, and the one that matters

Anurag Agrawal

SMB and Midmarket AI Adoption Moves Through 4 Stages. Partner Supply Thins at Every One.

Most AI pilots do not stall because the technology failed. They stall because the buyer and the partner are standing at different points on the same path. Drawing on studies of SMB, midmarket, and channel partner populations, I built the AI continuum to show where those points are, what gets bought at each one, and how customers pay for it.

Three years ago I published a slide mapping how small and midmarket firms moved along the cloud continuum. It traveled further than almost anything else I have produced, mostly because people put it into their own decks and argued with it. I have now rebuilt it for AI and agentic adoption, because the questions vendors and distributors are asking me this year are the same questions they asked about cloud, and the honest answer is again that the market is not one market moving at one speed.

Here is the argument in a sentence. Demand exists at every stage of AI adoption. Partner supply does not. And the gap between the two widens the further right you go.

Continuum diagrams are usually somebody's hypothesis drawn neatly. This one rests on Techaisle's 2026 survey programs across small business, midmarket, and channel partner populations, running to thousands of respondents globally, and on the qualitative work around them: structured interviews, vendor and distributor briefing sessions, and a large number of unstructured conversations with buyers and partners. The surveys established the stages and the volumes. The conversations established the sequence, and sequence is the part a questionnaire cannot reach.

Why a continuum instead of a maturity model

Maturity models rank companies. They tell a vendor which customers are ahead and which are behind, which is a comfortable thing to know and a useless thing to sell against. Every maturity model ends up recommending that the laggards catch up.

A continuum does something different. It maps what a customer actually buys at each stage, who they buy it from, and how they pay for it. That turns the picture into a route. A partner can look at a continuum and see the specific line item they are missing. A vendor can look at it and see which stage their program is funding and which stage their marketing is describing, and those are frequently not the same stage.

The version I have built runs on the same spine as the original: partner entry point across the top, partner revenue flywheel through the middle, end-point on the right, current state to future ready along the bottom. Four stage columns, with five layers of data underneath each one.

Anurag Agrawal

The Identity Profit Stack: How Cisco’s Secure MSP Center Turns the SMB Security Imperative into Recurring Margin

For partners serving the SMB and midmarket, the security conversation has changed in a way that resets the profit equation. Security has stopped being a discretionary line item that customers fund when they get around to it. The reason is not abstract. Identity-related attacks have moved to the center of how breaches happen, and attackers armed with stolen credentials and AI-assisted social engineering increasingly bypass multi-factor authentication by logging in rather than breaking in. The control surface that buyers most need to defend has shifted from the network to the identity itself, and the budget is following suit.

Techaisle’s 2026 SMB and Midmarket Security study shows that the organizations these partners serve are not only spending more on security, but also restructuring how they buy it. Over 60% of Core Midmarket organizations plan to increase security budgets by 5% or more in 2026, and 28% of the Upper Midmarket plan to increase budgets by more than 15%. The pattern reads as a structural reset rather than a fear-driven spike. Buyers have accepted that breach inevitability has moved downmarket, and that identity is now the control surface that matters, which is why protecting the identity plane ranks as the single highest security priority across the SMB market.

For the smaller partner and the MSP, that reset is the largest unclaimed annuity in the channel. The question is whether the partner has the architecture to capture it.

techaisle cisco identity profit stack

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