AI washing and the new currency of trust in the digital world
Artificial intelligence is rapidly becoming one of the most powerful symbols of technological progress. Across industries, organizations are investing in AI-driven solutions, businesses are incorporating AI into their products, and governments are exploring its potential to improve public services and economic productivity. Yet, as artificial intelligence gains prominence, a critical question emerges: how can society distinguish genuine innovation from the appearance of innovation? This is where the concept of AI washing becomes increasingly important.
AI washing refers to the practice of exaggerating, misrepresenting or making misleading claims about the use or capabilities of artificial intelligence. Similar to greenwashing, in which environmental credentials are overstated for commercial advantage, AI washing exploits public enthusiasm for a transformative technology. A product may be marketed as AI-powered when its capabilities are limited, while an organization may promote its AI adoption without clearly demonstrating how the technology contributes to its performance. The concern is not that every ambitious claim is misleading, but that technological language can sometimes advance faster than the evidence supporting it.
The implications extend far beyond marketing. When investors make decisions based on exaggerated AI claims, capital may flow towards perceived innovation rather than demonstrated value. When customers purchase products on the assumption that artificial intelligence offers capabilities that do not exist, confidence in legitimate technologies can suffer. Over time, this gap between promise and performance risks undermining the credibility of the wider AI ecosystem, including the work of researchers, entrepreneurs and businesses developing genuinely useful solutions.
Regulatory developments illustrate why this issue deserves serious attention. In the United States, the Securities and Exchange Commission has warned that misleading statements about the use of artificial intelligence can violate existing securities laws. In 2024, the SEC brought enforcement actions against two investment advisers over misleading claims concerning their use of AI. The Federal Trade Commission has also pursued companies over deceptive representations about AI-powered products and services. These actions demonstrate a fundamental principle: presenting a technology as innovative does not exempt its claims from scrutiny or established standards of accountability.
Trust, therefore, must become a central measure of technological progress. The OECD AI Principles emphasize transparency, explainability and accountability, including the importance of providing meaningful information about AI systems’ capabilities and limitations. These principles are not obstacles to innovation; they help create the conditions in which people can adopt new technologies with greater confidence. When organizations explain what their systems actually do, disclose relevant limitations and remain accountable for their outcomes, they strengthen the relationship between technological advancement and public trust.
The European Union has also advanced transparency requirements through its AI Act. As of 2 August 2026, relevant provisions under Article 50 began applying to covered AI systems and uses, including requirements concerning the identification of certain AI-generated or manipulated content and disclosure in specified circumstances. These rules address transparency risks rather than AI washing alone, but they reflect a broader recognition that people need reliable information about their interactions with artificial intelligence.
For Jordan, the global discussion presents an opportunity rather than an accusation. As the country continues to pursue digital transformation and develop its technology sector, the emerging lesson is that ambition becomes more valuable when supported by measurable outcomes. AI initiatives can be assessed through practical questions: Do they improve service quality? Do they increase productivity? Are their results independently verifiable? Are users informed about relevant limitations, and is human oversight maintained where decisions carry significant consequences? Such questions can help strengthen confidence among citizens, investors and international partners without diminishing the importance of experimentation or innovation.
This approach also matters for education and employment. Developing AI literacy means more than teaching people to use new tools; it means enabling them to evaluate technological claims critically. Universities, businesses and public institutions can contribute by promoting evidence-based assessment, responsible deployment and a clear distinction between adopting AI and merely advertising it. The objective should not be to discourage organizations from exploring artificial intelligence, but to ensure that genuine progress is recognized and rewarded.
Ultimately, trust may become one of the most valuable assets in the digital economy. Algorithms can be developed, products can be replicated and technological claims can be made with increasing ease. Credibility, however, must be earned through transparency, evidence and consistent performance. The future will not belong simply to those who claim to use artificial intelligence, but to those who demonstrate that it delivers meaningful value.
For countries seeking to strengthen their position in the digital world, including Jordan, the challenge is not merely to participate in the AI revolution. It is to help shape a culture in which innovation is judged by what it achieves, not by how convincingly it is presented. In an age when intelligence can be marketed as a brand, trust is the currency that gives technological progress its real worth.
The author is a specialist in educational technology
Artificial intelligence is rapidly becoming one of the most powerful symbols of technological progress. Across industries, organizations are investing in AI-driven solutions, businesses are incorporating AI into their products, and governments are exploring its potential to improve public services and economic productivity. Yet, as artificial intelligence gains prominence, a critical question emerges: how can society distinguish genuine innovation from the appearance of innovation? This is where the concept of AI washing becomes increasingly important.
AI washing refers to the practice of exaggerating, misrepresenting or making misleading claims about the use or capabilities of artificial intelligence. Similar to greenwashing, in which environmental credentials are overstated for commercial advantage, AI washing exploits public enthusiasm for a transformative technology. A product may be marketed as AI-powered when its capabilities are limited, while an organization may promote its AI adoption without clearly demonstrating how the technology contributes to its performance. The concern is not that every ambitious claim is misleading, but that technological language can sometimes advance faster than the evidence supporting it.
The implications extend far beyond marketing. When investors make decisions based on exaggerated AI claims, capital may flow towards perceived innovation rather than demonstrated value. When customers purchase products on the assumption that artificial intelligence offers capabilities that do not exist, confidence in legitimate technologies can suffer. Over time, this gap between promise and performance risks undermining the credibility of the wider AI ecosystem, including the work of researchers, entrepreneurs and businesses developing genuinely useful solutions.
Regulatory developments illustrate why this issue deserves serious attention. In the United States, the Securities and Exchange Commission has warned that misleading statements about the use of artificial intelligence can violate existing securities laws. In 2024, the SEC brought enforcement actions against two investment advisers over misleading claims concerning their use of AI. The Federal Trade Commission has also pursued companies over deceptive representations about AI-powered products and services. These actions demonstrate a fundamental principle: presenting a technology as innovative does not exempt its claims from scrutiny or established standards of accountability.
Trust, therefore, must become a central measure of technological progress. The OECD AI Principles emphasize transparency, explainability and accountability, including the importance of providing meaningful information about AI systems’ capabilities and limitations. These principles are not obstacles to innovation; they help create the conditions in which people can adopt new technologies with greater confidence. When organizations explain what their systems actually do, disclose relevant limitations and remain accountable for their outcomes, they strengthen the relationship between technological advancement and public trust.
The European Union has also advanced transparency requirements through its AI Act. As of 2 August 2026, relevant provisions under Article 50 began applying to covered AI systems and uses, including requirements concerning the identification of certain AI-generated or manipulated content and disclosure in specified circumstances. These rules address transparency risks rather than AI washing alone, but they reflect a broader recognition that people need reliable information about their interactions with artificial intelligence.
For Jordan, the global discussion presents an opportunity rather than an accusation. As the country continues to pursue digital transformation and develop its technology sector, the emerging lesson is that ambition becomes more valuable when supported by measurable outcomes. AI initiatives can be assessed through practical questions: Do they improve service quality? Do they increase productivity? Are their results independently verifiable? Are users informed about relevant limitations, and is human oversight maintained where decisions carry significant consequences? Such questions can help strengthen confidence among citizens, investors and international partners without diminishing the importance of experimentation or innovation.
This approach also matters for education and employment. Developing AI literacy means more than teaching people to use new tools; it means enabling them to evaluate technological claims critically. Universities, businesses and public institutions can contribute by promoting evidence-based assessment, responsible deployment and a clear distinction between adopting AI and merely advertising it. The objective should not be to discourage organizations from exploring artificial intelligence, but to ensure that genuine progress is recognized and rewarded.
Ultimately, trust may become one of the most valuable assets in the digital economy. Algorithms can be developed, products can be replicated and technological claims can be made with increasing ease. Credibility, however, must be earned through transparency, evidence and consistent performance. The future will not belong simply to those who claim to use artificial intelligence, but to those who demonstrate that it delivers meaningful value.
For countries seeking to strengthen their position in the digital world, including Jordan, the challenge is not merely to participate in the AI revolution. It is to help shape a culture in which innovation is judged by what it achieves, not by how convincingly it is presented. In an age when intelligence can be marketed as a brand, trust is the currency that gives technological progress its real worth.
The author is a specialist in educational technology
Artificial intelligence is rapidly becoming one of the most powerful symbols of technological progress. Across industries, organizations are investing in AI-driven solutions, businesses are incorporating AI into their products, and governments are exploring its potential to improve public services and economic productivity. Yet, as artificial intelligence gains prominence, a critical question emerges: how can society distinguish genuine innovation from the appearance of innovation? This is where the concept of AI washing becomes increasingly important.
AI washing refers to the practice of exaggerating, misrepresenting or making misleading claims about the use or capabilities of artificial intelligence. Similar to greenwashing, in which environmental credentials are overstated for commercial advantage, AI washing exploits public enthusiasm for a transformative technology. A product may be marketed as AI-powered when its capabilities are limited, while an organization may promote its AI adoption without clearly demonstrating how the technology contributes to its performance. The concern is not that every ambitious claim is misleading, but that technological language can sometimes advance faster than the evidence supporting it.
The implications extend far beyond marketing. When investors make decisions based on exaggerated AI claims, capital may flow towards perceived innovation rather than demonstrated value. When customers purchase products on the assumption that artificial intelligence offers capabilities that do not exist, confidence in legitimate technologies can suffer. Over time, this gap between promise and performance risks undermining the credibility of the wider AI ecosystem, including the work of researchers, entrepreneurs and businesses developing genuinely useful solutions.
Regulatory developments illustrate why this issue deserves serious attention. In the United States, the Securities and Exchange Commission has warned that misleading statements about the use of artificial intelligence can violate existing securities laws. In 2024, the SEC brought enforcement actions against two investment advisers over misleading claims concerning their use of AI. The Federal Trade Commission has also pursued companies over deceptive representations about AI-powered products and services. These actions demonstrate a fundamental principle: presenting a technology as innovative does not exempt its claims from scrutiny or established standards of accountability.
Trust, therefore, must become a central measure of technological progress. The OECD AI Principles emphasize transparency, explainability and accountability, including the importance of providing meaningful information about AI systems’ capabilities and limitations. These principles are not obstacles to innovation; they help create the conditions in which people can adopt new technologies with greater confidence. When organizations explain what their systems actually do, disclose relevant limitations and remain accountable for their outcomes, they strengthen the relationship between technological advancement and public trust.
The European Union has also advanced transparency requirements through its AI Act. As of 2 August 2026, relevant provisions under Article 50 began applying to covered AI systems and uses, including requirements concerning the identification of certain AI-generated or manipulated content and disclosure in specified circumstances. These rules address transparency risks rather than AI washing alone, but they reflect a broader recognition that people need reliable information about their interactions with artificial intelligence.
For Jordan, the global discussion presents an opportunity rather than an accusation. As the country continues to pursue digital transformation and develop its technology sector, the emerging lesson is that ambition becomes more valuable when supported by measurable outcomes. AI initiatives can be assessed through practical questions: Do they improve service quality? Do they increase productivity? Are their results independently verifiable? Are users informed about relevant limitations, and is human oversight maintained where decisions carry significant consequences? Such questions can help strengthen confidence among citizens, investors and international partners without diminishing the importance of experimentation or innovation.
This approach also matters for education and employment. Developing AI literacy means more than teaching people to use new tools; it means enabling them to evaluate technological claims critically. Universities, businesses and public institutions can contribute by promoting evidence-based assessment, responsible deployment and a clear distinction between adopting AI and merely advertising it. The objective should not be to discourage organizations from exploring artificial intelligence, but to ensure that genuine progress is recognized and rewarded.
Ultimately, trust may become one of the most valuable assets in the digital economy. Algorithms can be developed, products can be replicated and technological claims can be made with increasing ease. Credibility, however, must be earned through transparency, evidence and consistent performance. The future will not belong simply to those who claim to use artificial intelligence, but to those who demonstrate that it delivers meaningful value.
For countries seeking to strengthen their position in the digital world, including Jordan, the challenge is not merely to participate in the AI revolution. It is to help shape a culture in which innovation is judged by what it achieves, not by how convincingly it is presented. In an age when intelligence can be marketed as a brand, trust is the currency that gives technological progress its real worth.
The author is a specialist in educational technology
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AI washing and the new currency of trust in the digital world
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