AI Isn't One Thing. It's a Toolbox.

The payoff comes from matching the right tool to the right job, not just reaching for the newest one.

0 %

of companies are overspending on AI

0 %

of companies plan to spend more

< 1 %

know why

AI in the Workplace A report for 2025 | McKinsey

Before you hand off another process to AI, ask one question:  does it actually belong here? It's not always an immediate yes.

Automation / RPA

Best for: Repetitive tasks that must be done the same way, every time, with zero room for error.

Rarely breaks on its own — usually fails only when something external changes

Delivers accurate results without needing to explain how it got there

$ 0 B

RPA market in 2024 – up 18% year-over-year, even as GenAI and agentic tools crowd the conversation

Tangoe's automation processes invoices in 8 seconds. By hand: 5–10 minutes.

Machine Learning

Best for: Crunching mountains of data to spot patterns and make predictions.

15-20%

of telecom invoices contain billing errors, usually favoring the carrier

Needs volume and repetition to learn from — without a pattern, prediction is poor

Learns behavior patterns (like a vendor’s typical delay) to work smarter, not harder

Tangoe's ML catches rate discrepancies and inactive lines still being billed, putting money back in the budget.

Generative AI (GenAI)

Best for: Turning complex information into something a person can understand and act on.

Interprets rather than calculates — a risk when the data carries real financial stakes

Best used for: “Here’s what broke, why, and what to do next”

0 %

of companies see no EBIT impact without integrated ML + GenAI

Tangoe One's built-in AI assistant delivers instant financial insights for scenario planning, root-cause analysis, and decision support.

Agentic AI

Best for: Complex, multi-step, multi-system work that also needs a clean audit trail — not full autonomy over a whole function.

0 %+

of agentic AI projects are predicted to be canceled by 2027

Only 130 of the thousands of vendors claiming “agentic AI” are genuinely agentic (Gartner)

60% of agentic spend goes toward the system checking its own work, not the task itself

It costs 5–30x the tokens of a standard GenAI interaction, so it earns its keep in narrow, well-bounded workflows — procurement exceptions, dispute handling — not wide-open autonomy. Not a hard no. Okay to wait and see.

What Tool Is Best? Run Your Problem Through 5 Decision Factors.

Cost: Is it solving something human effort genuinely can’t? Remember: AI costs move differently and you need to measure against ROI continuously.

Reliability: Do you need the same right answer, every time, consistently?

Scale: Does the volume/speed exceed what a human team can do manually? (Small-scale tests hide problems that only surface under real load).

Real-world resilience: Can it bend without breaking when a vendor is late or a system changes without warning?

Long-term viability: Will it still be supported, and supportable, two years from now?

It's not about solving every problem with AI. It's about adding the right capability where it makes sense.

AI, automation, or something else? Decades of building technology expense management taught us that the newest tool isn’t always the right one, and that discipline shapes every part of Tangoe One.

AI Isn't One Thing. It's a Toolbox.