News
- Lake Ontario is now Lake America in the US via an executive order
- Google Maps has updated its maps to reflect the change
- Viewing the map from outside the US still shows the original name
Some 18 months on from the controversial renaming of the Gulf of Mexico, another edit has been made to Google Maps at the behest of US President Donald Trump: Lake Ontario, spread across the US-Canadian border, is now Lake America.
Or rather, it is if you're viewing Google Maps from inside the US (via Gizmodo) — the rest of the world will still see the Great Lake labeled as it has been since at least the 17th century. The name Ontario most likely comes from the Iroquoian word Kaniatarí:io or Oniatarí:io meaning "lake of shining waters" or "beautiful lake", as per Wikipedia.
The name change is the result of an executive order from the White House, as President Trump bickers with Canada over trade tariffs. In response, Canadian authorities have installed a large new sign at the lake (via the BBC), reading 'Lake Ontario. Now and Always'.
Reactions on Reddit are calling the switch "beyond ridiculous" and "braindead", though some commenters are pointing out that Google is obliged to follow the lead of the US Board on Geographic Names (part of the United States Geological Survey).
Google respondsNew York won’t be calling it that. https://t.co/FJQonEk8tIAugust 27, 2026
For its part, Google has also chimed in to say that it has to follow "official government sources" when it comes to place names, saying that "these updates follow our long-standing policy for bodies of water with names that vary from country to country, and are starting to roll out now".
"People using Maps in the US will see 'Lake America', those in Canada will continue to see 'Lake Ontario', and those outside of the US and Canada will see both names," according to the official blog post from Google Maps on the matter.
However, not everyone is towing the line on this: New York State Governor Kathy Hochul took to social media to declare that "New York won't be calling it [Lake America]", so there are going to be some pockets of resistance regarding the change.
As yet the change hasn't rolled out on Apple Maps, but presumably it'll eventually have to comply with the official government, and start renaming Lake Ontario depending on where in the world you're viewing the map from.
For anyone working in IT and familiar with SaaS sprawl, the idea we’ll soon end up with agent sprawl may set off alarm bells. Agent sprawl refers to the rapid, uncoordinated deployment of AI agents across departments, each built on different models, governed by different rules, and often disconnected from core business workflows.
But while SaaS sprawl caught enterprises off guard, this time organizations have no excuse, and need to put measures in place now to avoid repeating the same mistakes. However, right now, most organizations are building agents in isolation and optimizing for local productivity rather than enterprise value.
Thankfully, with the right control layer funneling every agent through the same governance and security standards within an organization, the agent-powered future can be far safer, scalable and simple.
Agent sprawl is inevitableJust like SaaS before it, agent sprawl is already happening. Each department within organizations is experimenting with different agent technologies to address specific challenges or work more efficiently.
A sales team may deploy a CRM-based AI assistant to qualify leads, while developers build their own coding agents, and marketing adopts a separate content generation tool. Each delivers local value, but none are aligned or connected to the other, creating a familiar-looking sprawl.
This fragmentation introduces a range of challenges that will only increase over time. With no single owner responsible for how agents are deployed or monitored, there’s a lack of governance and oversight. Security risks increase as agents gain access to sensitive systems without consistent controls.
Teams may unknowingly duplicate efforts, solving the same problems in parallel with different tools. At the same time, many agents are deployed without clear links to business outcomes or understanding the wider context, making it difficult to measure return on investment and distinguish meaningful innovation from experimentation. Lots of AI tools may be exciting, but deliver far more style than substance.
Is sprawl inevitable? Yes, probably. So the question now becomes, how do we control it?
The role of orchestrationHaving an orchestration layer can bring order to this complexity by creating consistency in how agents are governed, secured and deployed across the business. For SaaS applications, orchestration provides visibility into what tools already exist and gives a clear view of enterprise workflows.
With agents, it outlines what agents are already available and how they operate, while also controlling how they access data, tools and existing technology. Orchestration is the critical element that turns agents from experiments into scalable business infrastructure, for example, assigning agents to business workflows and measuring their performance against real outcomes.
Too often, we see enterprises experimenting with different agents that have no connection to the core business processes and goals, meaning they fail to deliver any ROI. For example, some portions of a business simply do not require AI technology and will unlikely see benefits in the same way as another department. Orchestration can unearth and filter out agents that are unnecessary, saving businesses money.
Building trust in AI-driven enterpriseRather than trusting individual agents, organizations should focus on trusting the system that governs them.
This is where orchestration becomes a trust layer, ensuring every agent operates within clearly defined boundaries with consistent oversight and accountability. Instead of individual teams managing risk in siloes, organizations can centralize control while still enabling innovation across different departments and business functions.
In the same way orchestration brought order to SaaS sprawl, it can do the same for the next wave of enterprise AI. It brings the same ease, security and integration with existing SaaS tools, while ensuring only high-value agents make it into production, supporting innovation and keeping within the business goals and purpose.
As agents become embedded across every function, orchestration will shift from a technical layer to a core enterprise capability. The winners will be those who can control, connect and trust their agents at scale.
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