Hello There! First, an apology: this is the August edition… arriving in September. August was anything but quiet on the technology front, and that delayed us by a few days 😊.
In this issue: Why you are probably overwhelmed with AI, moving technology announcements, geting your data ready for conference season, even more capable AI, and a caution: don’t reduce headcount quite yet.
The View from the Edge
The AI fog: Overwhelmed yet?
If AI feels harder to follow, there is now a term for it: AI fog. Harvard Business Review uses it for the uncertainty created when technology changes faster than we can confidently plan.
That fits the moment. New models, agents and features arrive every week, with different strengths, prices and capabilities. Essentially all agents can browse, remember context, use computers and work in the background - but none is perfect and the rankings keep moving.
The gap between promise and operating reality is also clearer. After layoffs and hiring freezes partly tied to AI expectations, companies including Alphabet, ServiceNow, Booz Allen and Robert Half are reportedly hiring again. AI has improved enormously; turning it into reliable processes still needs people.
So what should the CEO of a moving company do with all of this?
Stay focused on what works today.
Avoid five-year bets on the winning platform, your future organization chart or how many jobs an agent might replace. Make smaller decisions that can survive being wrong.
Start with a business problem, not an AI product.
Pick a real workflow: sales follow-up, survey summaries, invoice checks, move-file search, data cleaning, customer communication or repetitive admin.
Test what actually works.
There is no single "best AI." Tools differ by capability, integration and cost. If you want to compare them, OpenRouter's model comparison is useful - and also a good illustration of how quickly the AI fog returns.
For most moving companies, keep it simple:
Choose one workflow or problem.
Test two or three tools on the same real task.
Measure time saved, quality and cost.
Keep a human involved where mistakes matter.
Use the winner for that task - not necessarily for everything.
Retest the market in six months.
IBM's 2026 CEO Study makes a similar point: orchestrate human and artificial intelligence, tailor the AI mix, and expect an unpredictable future.
You do need to move. Use what is valuable today, solve real problems, keep commitments flexible and give yourself permission to change the answer six months from now.
Industry Tech Watch
Moveware expands its product offering. Public Moveware resources show development across areas including Online Docs, Self Survey, its REST API and the recently released Moveware Go mobile app (Apple, Android and the Microsoft Store). Moveware is also reportedly previewing additional capabilities to customers, although some appear to remain roadmap items rather than confirmed production functionality. For more information on Moveware’s current and upcoming capabilities, contact Moveware directly.
One more AI survey tool joins the field. I recently found MoveBlueprint, yet another AI-powered video survey option: the customer records a walkthrough, the system creates the inventory and can feed it into the mover's CRM. My running count is now 18 AI survey apps. If you do not feel like investigating all of them yourself, contact me and I can help narrow the field.
Move AI acquired. Move AI, an AI-powered moving concierge, was acquired by National Holding Company, parent of National Van Lines and owner of moving.com.
FIDI-FAIM remote audits are here to stay. FIDI says remote audits are now permanent for existing Affiliates; first-time applicants remain onsite. Remote audits require electronic documentation, online procedure demonstrations and video facility inspections. The takeaway: digital move files and evidence are increasingly part of being audit ready. Read the FIDI Focus article.
Yembo completes CMMC 2.0 Level 2 self-assessment. Yembo says it has completed the self-assessment for controls protecting Controlled Unclassified Information used in military moves. This is particularly relevant to U.S. TSPs, with the cited requirement calling for Level 2 compliance in SPRS by March 1, 2027. Read the announcement.
AI is moving inside the moving CRM. SmartMoving has launched TOB-E, Supermove has announced Autopilot, and EDC already offers MERCED. The upside: native AI sits close to operational data and workflows. The downside: your CRM provider may also choose the model for you, limiting flexibility as models change quickly.
Tools and Workflows
Mapping, Reciprocity, Voice, and more
Reciprocity tracking without another spreadsheet. After multiple readers asked if we knew of an easier way to calculate and show agent trade reciprocity, and not finding a suitable solution for them - we decided to build one! We built a simple Reciprocity Tracking tool for the conference season coming up. Want it set up before the conferences? Contact us.
A carbon-emissions platform built for moving and mobility. ecolegIT calculates and tracks CO2 compensation by move, provides digital certificates and gives companies a portal for monitoring compensation and audit status. Worth a look for movers facing more detailed sustainability requests from corporate clients.
Better visibility into when a UK house move will actually happen. The myMoveToday platform connects removals firms to live property-transaction data and can alert them when exchange or completion dates change, giving operations teams earlier warning to adjust schedules and vehicle capacity.
Speak Up. Voice recognition is becoming practical for operational work. Google Workspace is expanding voice functionality across Gmail, Docs and Keep. That made me think of inventories: surveyors and crews already describe what they see, so why not turn that speech into structured inventory data, packing lists or survey notes? We test-built a simple Voice Inventory workflow for this. Read more here, or contact us to join the beta.
Finally, you can stop having to remember filenames! Clipto lets you search files by describing what you need across documents, images, video and audio. For movers, that could mean "the survey where the customer had a grand piano going to Singapore" instead of remembering Smith_2024_Final_v3.pdf. Best of all, it can run locally, so sensitive move data does not need to be uploaded online.
A way to find money you may be accidentally giving away. Freehand focuses in part on logistics spend, comparing invoices against contracts, rate cards and operational data. For movers, that means carrier invoices, destination-agent charges, storage and subcontractor costs against the actual move and agreed rates.
Better Google Maps for movers. First, Large Vehicle Routing is now available in the U.S. for trucks and other large commercial vehicles, accounting for vehicle dimensions, weight, axle count and road restrictions, with truck-specific ETAs and multi-stop planning. Secondly, Google is also innovating on how drivers interact with Maps through more conversational, voice-based interaction with Gemini. Imagine a driver asking for a safe stop between two deliveries while avoiding a difficult city-centre approach. The simple takeaway: make sure your drivers know what these tools can now do.
The Learning Centre
Clean your <reciprocity> data with AI
AI is getting better at understanding, managing and cleaning data, with tools that can work directly in files, Excel and Google Sheets. With conference season around the corner, here’s a practical example of how to use this: cleaning your reciprocity data.
1. Export your trade data. Export the underlying move data from your CRM or move-management system into Excel or CSV.
2. Upload it to your AI assistant. Use ChatGPT, Claude, Gemini or whichever AI you normally work with.
3. Give it clear instructions. Describe the data problems and the fix you want. Example:
This spreadsheet contains moves exchanged between my moving company and overseas agents. I use it to measure reciprocity: how much business we send to each agent compared with how much they send to us, including year-over-year analysis.
Clean the data before I use it. Issues to fix:
- Agent names vary slightly. Standardize obvious variations to one name and flag uncertain matches.
- Moves appear more than once because of multiple service types. Count the move once for reciprocity and add service volumes to one job line.
- Dates are inconsistent or stored as text. Convert them to real dates using one consistent format.
- Countries are assigned to the wrong regions. Standardize countries against the correct region assignments.
- Units mix imperial, metric, volume and weight. Convert to Imperial and show volume only, using 6.5 lb per cu ft.
Keep the original file unchanged. Create a cleaned version plus a short list of anything changed or unresolved. Do not guess where the data is unclear - flag it for review.4. ALWAYS review the data before you use it. Check the change log produced, and anything the AI flagged before relying on the cleaned file.
Worth your Attention
Have we reached the singularity?
AI capability is increasingly about doing digital work. OpenAI is now talking about an AGI era with GPT-6 Astra, while everyday assistants are moving beyond answers: ChatGPT Work can work across apps, files and the web; Claude Cowork can browse and continue longer tasks; and Gemini Spark can use Chrome and, with permission, logged-in accounts.
But HR teams around the world are quickly recognizing that people are not as easily replaceable as some predicted. After layoffs and hiring freezes partly justified by AI expectations, some large employers are hiring again. The issue is not that AI failed; turning impressive demos into dependable business processes is harder than expected.
That may mean increased productivity rather than replacement. OpenAI's research on "task crossover" found that 43.5% of occupation-specific ChatGPT messages involved work normally associated with another occupation. A salesperson can analyze data, a marketer can troubleshoot a website, or an operations employee can create something that once required IT. For movers, one employee may increasingly do work that previously needed another role or department.
Cost keeps changing too. Cheaper models are improving, and companies are routing straightforward work to lower-cost AI while reserving frontier models for harder tasks. The trend has been described as "diminishing model returns": if several models can handle an everyday task, paying for the smartest one every time may make little sense.
Automation may be the clearest lesson. Companies successfully deploying agents within real-world risk, legal and compliance requirements are doing almost the opposite of "automate everything": using small, single-responsibility agents, keeping logs and retaining human approval before important actions.
AI is getting more capable, more autonomous and often cheaper. The trick may simply be giving it a smaller job. For a mover: start with "check this move file for missing documents," "compare this supplier invoice against the agreed rate," or "prepare tomorrow morning's exception report" - not "run my operations department."
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Until next (well really… this same) month,
Ramiro Quiros