Latest

The Ethics of AI in Hiring: How to Eliminate Bias and Build a Fairer Workforce

Artificial Intelligence (AI) is reshaping the recruitment landscape, with nearly 99% of Fortune 500 companies utilising some form of automation in their hiring processes. These systems streamline application reviews and candidate assessments, enhancing efficiency and reducing costs. However, as organisations increasingly adopt these technologies, concerns around algorithmic discrimination and AI bias in hiring have grown. Research shows alarming statistics on AI bias in hiring. AI-powered tools preferred white-associated.

Read more
Recommended for you
Blogs
The Ethics of AI in Hiring: How to Eliminate Bias and Build a Fairer Workforce

Artificial Intelligence (AI) is reshaping the recruitment landscape, with nearly 99% of Fortune 500 companies utilising some form of automation in their hiring processes. These systems streamline application reviews and candidate assessments, enhancing efficiency and reducing costs. However, as organisations increasingly adopt these technologies, concerns around algorithmic discrimination and AI bias in hiring have grown. Research shows alarming statistics on AI bias in hiring. AI-powered tools preferred white-associated.

Read more
AI-Powered Water Management: Enhancing Efficiency & Sustainability

With over 2.2 billion people lacking access to safe drinking water globally, the demand for improved water management systems has never been more urgent. In Europe, where stringent regulations like the EU Water Framework Directive govern water quality and availability, integrating AI into water treatment processes is essential. AI can offer water utilities the ability to predict problems before they occur, optimise the use of limited resources and ensure service reliability, even in the face of climate change and regulatory demands.

Read more
Understanding AI Security Threats: How to Protect Your Systems and Data

As artificial intelligence (AI) systems become integral to business operations, understanding the security threats associated with these technologies is essential. AI security encompasses practices designed to protect these systems from unauthorised access, tampering, and malicious attacks. In fact, according to IBM, organisations without AI security face an average data breach cost of USD 5.36 million, which is 18.6% higher than the average cost for all organisations.

Read more
Future-Proofing Supply Chains with AI Governance and Transparency

The global AI in manufacturing market is expected to reach $20.8 billion by 2028, yet its rapid adoption comes with risks—ranging from biased predictive models in supply chains to cybersecurity threats in automated systems. In this context, AI governance, supply chain risk management, and transparency are critical. AI-driven automation improves efficiency, but manufacturers must mitigate risks to avoid production disruptions, unethical sourcing practices, and compliance violations.

Read more
Maximising Competitive Advantage Through AI Adoption: A Strategic Approach for Organisations

A successful AI strategy requires comprehensive governance frameworks addressing risks related to bias and accountability. Organisations should implement specific risk management strategies, such as regular audits of AI systems and employee training focused on ethical AI practices. By proactively managing these potential pitfalls, organisations safeguard their reputations and foster stakeholder confidence in their AI initiatives.

Read more
The Ethics of AI: Why Human-in-the-Loop Systems are the Key to Fair & Accountable AI

Ethical AI deployment requires proactive strategies to address bias, transparency, and accountability. Human-in-the-Loop (HITL) AI is increasingly recognised as a safeguard against unintended consequences, ensuring AI decisions align with ethical and regulatory standards. According to Science Direct, integrating human oversight enhances interpretability and trust, allowing organisations to scale AI responsibly.

Read more
Unlocking the ROI of AI: Manoeuvring the Complex Landscape of AI Integration, with Camilo Sandoval (Former Senior White House Advisor)

Camilo Sandoval, former Senior White House Advisor, sheds light on the opaque nature of AI systems. This “black box” nature of AI solutions could be particularly concerning in sectors such as healthcare, finance, law, and government, where transparency is paramount. There is a risk that data biases within these systems can lead to unjust outcomes, such as wrongful allocation of federal benefits.

Read more
Case studies
Navigating AI Risks: Lessons from Adobe's Terms of Service Backlash

In the dynamic landscape of corporate software, recent events surrounding Adobe's Terms of Service (ToS) changes serve as a stark reminder of the evolving risks businesses face, especially with the incorporation of AI. This controversy, while specific to Adobe, underscores broader issues pertinent to AI adoption and highlights the critical need for heightened awareness and proactive risk management strategies within organisations.

Read more
Whitepapers
UNLOCKING THE POWER OF AI IN HEALTHCARE: Managing Data, Risk, and Compliance

Artificial intelligence (AI) has the potential to revolutionise healthcare by improving diagnostics, treatment options, and operational efficiencies. However, for AI to reach its full potential in this sensitive industry, several critical challenges must be addressed. These challenges include ensuring the availability of high-quality data, adhering to complex regulatory frameworks, and managing the risks inherent in deploying AI systems.

Read more

All

Blogs

Case studies

White papers

Blog
The Ethics of AI in Hiring: How to Eliminate Bias and Build a Fairer Workforce

Artificial Intelligence (AI) is reshaping the recruitment landscape, with nearly 99% of Fortune 500 companies utilising some form of automation in their hiring processes. These systems streamline application reviews and candidate assessments, enhancing efficiency and reducing costs. However, as organisations increasingly adopt these technologies, concerns around algorithmic discrimination and AI bias in hiring have grown. Research shows alarming statistics on AI bias in hiring. AI-powered tools preferred white-associated.

Read more
Blog
AI-Powered Water Management: Enhancing Efficiency & Sustainability

With over 2.2 billion people lacking access to safe drinking water globally, the demand for improved water management systems has never been more urgent. In Europe, where stringent regulations like the EU Water Framework Directive govern water quality and availability, integrating AI into water treatment processes is essential. AI can offer water utilities the ability to predict problems before they occur, optimise the use of limited resources and ensure service reliability, even in the face of climate change and regulatory demands.

Read more
Blog
Understanding AI Security Threats: How to Protect Your Systems and Data

As artificial intelligence (AI) systems become integral to business operations, understanding the security threats associated with these technologies is essential. AI security encompasses practices designed to protect these systems from unauthorised access, tampering, and malicious attacks. In fact, according to IBM, organisations without AI security face an average data breach cost of USD 5.36 million, which is 18.6% higher than the average cost for all organisations.

Read more
Blog
Future-Proofing Supply Chains with AI Governance and Transparency

The global AI in manufacturing market is expected to reach $20.8 billion by 2028, yet its rapid adoption comes with risks—ranging from biased predictive models in supply chains to cybersecurity threats in automated systems. In this context, AI governance, supply chain risk management, and transparency are critical. AI-driven automation improves efficiency, but manufacturers must mitigate risks to avoid production disruptions, unethical sourcing practices, and compliance violations.

Read more
Blog
Maximising Competitive Advantage Through AI Adoption: A Strategic Approach for Organisations

A successful AI strategy requires comprehensive governance frameworks addressing risks related to bias and accountability. Organisations should implement specific risk management strategies, such as regular audits of AI systems and employee training focused on ethical AI practices. By proactively managing these potential pitfalls, organisations safeguard their reputations and foster stakeholder confidence in their AI initiatives.

Read more
Blog
The Ethics of AI: Why Human-in-the-Loop Systems are the Key to Fair & Accountable AI

Ethical AI deployment requires proactive strategies to address bias, transparency, and accountability. Human-in-the-Loop (HITL) AI is increasingly recognised as a safeguard against unintended consequences, ensuring AI decisions align with ethical and regulatory standards. According to Science Direct, integrating human oversight enhances interpretability and trust, allowing organisations to scale AI responsibly.

Read more
White paper
UNLOCKING THE POWER OF AI IN HEALTHCARE: Managing Data, Risk, and Compliance

Artificial intelligence (AI) has the potential to revolutionise healthcare by improving diagnostics, treatment options, and operational efficiencies. However, for AI to reach its full potential in this sensitive industry, several critical challenges must be addressed. These challenges include ensuring the availability of high-quality data, adhering to complex regulatory frameworks, and managing the risks inherent in deploying AI systems.

Read more
Case study
Navigating AI Risks: Lessons from Adobe's Terms of Service Backlash

In the dynamic landscape of corporate software, recent events surrounding Adobe's Terms of Service (ToS) changes serve as a stark reminder of the evolving risks businesses face, especially with the incorporation of AI. This controversy, while specific to Adobe, underscores broader issues pertinent to AI adoption and highlights the critical need for heightened awareness and proactive risk management strategies within organisations.

Read more
Blog
Unlocking the ROI of AI: Manoeuvring the Complex Landscape of AI Integration, with Camilo Sandoval (Former Senior White House Advisor)

Camilo Sandoval, former Senior White House Advisor, sheds light on the opaque nature of AI systems. This “black box” nature of AI solutions could be particularly concerning in sectors such as healthcare, finance, law, and government, where transparency is paramount. There is a risk that data biases within these systems can lead to unjust outcomes, such as wrongful allocation of federal benefits.

Read more
Blog
Responsible AI: Tackling risks and building trust in AI

Responsible AI involves an ethical and legal framework ensuring the safe, trustworthy, and fair application of artificial intelligence. It involves governance frameworks, transparency promotion, and accountability measures to mitigate biases and uphold principles of fairness and reliability. Real-world initiatives by companies like Microsoft and IBM exemplify responsible AI adoption through comprehensive principles, tools, and...

Read more

AI news & stories

We’ll send you the best AI & Tech content, only once a month. We Promise!