Nigeria's customs service will use AI to track those who discredit it: useful against fraud, sensitive if it monitors criticism

By PRNigeria News · November 1, 2026.

The Nigeria Customs Service (NCS) has announced it will step up its response to fake news, online scams and misleading information using artificial intelligence and digital data-tracking tools. According to the outlet, the technology will be used to monitor public sentiment, establish the facts about the agency's activities and identify those behind hoaxes that could damage its reputation.

The announcement was made by the national public relations officer, Deputy Comptroller Abdullahi Maiwada, on behalf of Comptroller-General Adewale Adeniyi. It came at the Neccipr 2026 roundtable, held in Lagos on Friday, October 30, under the theme “Algorithmic Influence and Public Relations.” Another outlet, Independent Newspaper Nigeria, reports the same announcement with similar framing.

Maiwada said AI is already used in core customs operations: assessing the risk of imported goods, classifying shipments by risk level and guiding appropriate interventions. According to him, it has also been used in strategic communication. He added that the Service is working with other agencies to identify and stop those who spread misleading information. The report does not specify which tools are used, what data is collected or what safeguards are in place.

At the same roundtable, the organizer, Nkechi Ali-Balogun, warned that algorithms can shape political narratives and amplify conspiracy theories. Her question was: “When machines decide what we see, who is really shaping the Nigerian mind?”

**Our take**

Our thesis: the announcement blends two uses of AI that deserve very different judgments, and they should not be treated as one.

The first is solid and uncontroversial. Classifying cargo by risk is a classic machine-learning problem, and a customs agency that does it well catches more contraband with less friction for legitimate trade. It is the kind of quiet, useful administrative improvement that drives a country's productivity.

The second is more delicate. Analyzing public sentiment is standard practice for any organization. But the goal of identifying those behind misleading information that could damage the Service's reputation is framed around the institution's reputation, not around harm to citizens, as would be the case with a scam. Digital fraud is a crime. Uncomfortable criticism, even if inaccurate, is not. When the same tool serves both purposes, everything hinges on who defines what is “misleading.”

Broadly, this pattern recurs in many countries: a capability created to fight fraud and disinformation expands into managing institutional image. We are not saying that is the intention here; the article offers no evidence either way. We are saying that the announcement, as reported, does not provide the safeguards that would allow the two to be told apart.

There is also a useful irony. The roundtable itself examined how algorithms shape opinion. An institution that monitors that opinion with algorithms enters the very loop it claims to analyze.

**What should be required**

For this kind of deployment to be defensible, a few conditions suffice: public criteria for what counts as misleading, a separation between scams (a crime) and criticism (a right), independent oversight and transparency about what data is collected. None of these prevents going after real fraud.

In the short term, states with weak institutions will adopt these tools faster than the frameworks that constrain them. In the long term, the same AI used for surveillance today could also be what audits the watchers, verifies facts at scale and makes it harder to scam citizens. Which way it tips depends on the rules, not the technology.