At Qlik Connect 2024, the Qlik AI Council issued a clear warning to businesses: adopting AI without ensuring data integrity is a risky gamble. During their panel session, industry leaders highlighted that neglecting data quality can lead to serious consequences, including operational failures, regulatory breaches, and financial losses. The Council’s joint statement emphasizes the need for capable data foundations that enable effective, outcome-driven, and lower-risk AI adoption. Ensuring data diversity, timeliness, accuracy, security, discoverability, and ease of consumption by machines is essential for successful AI initiatives.
The Qlik AI Council outlined two primary risks for businesses that fail to prioritize data integrity and analytics foundations in their AI adoption strategies:
Slow Adoption and Competitive Lag: Companies that neglect the integrity of their data and analytics foundations will be hesitant to adopt AI, causing them to fall behind their competitors. This delay in AI adoption can result in missed opportunities and a widening gap that becomes increasingly difficult to bridge.
Adoption Without Integrity Leads to Crises: Businesses that rush to implement AI without focusing on the caliber and quality of their data risk facing severe consequences. These can include governance issues, regulatory breaches, inefficiencies, and poor decision-making driven by biased or inaccurate data. Such missteps can lead to significant financial losses and reputational damage.
Reflecting on the current state of enterprise AI adoption, members of the Qlik AI Council commented:
“Ensuring data integrity is crucial for the responsible deployment of AI. Without accurate, diverse, and secure data, AI systems have a greater propensity to perpetuate biases and lead to significant ethical issues,” noted Dr. Rumman Chowdhury, a leading expert in ethical AI development. “Transparency, fairness, and accountability must be embedded at every stage of AI development to build trust and ensure the technology benefits all users.”
“Generative AI has the potential to revolutionize industries and drive competitiveness, but its benefits hinge on maintaining public trust,” emphasized Nina Schick, a leading authority on AI and geopolitics. “Ensuring the authenticity and reliability of AI-generated content is crucial to prevent misinformation and uphold the integrity of our digital landscape.”
“Implementing AI in a socially responsible manner is critical for aligning with global sustainability goals,” stated Kelly Forbes, a distinguished expert in AI governance. “Businesses must adopt responsible and sustainable data practices to ensure that AI contributes to long-term economic growth and societal well-being. This approach not only mitigates risks but also fosters trust and accountability.”
“Advanced AI methodologies, like graph neural networks, hold immense potential for solving complex business problems,” noted Dr. Michael Bronstein, a pioneer in this field. “High-quality and well-structured data is essential for these technologies to succeed, enabling innovative applications that range from drug discovery to interpreting non-human communication and can potentially lead to transformative outcomes”
The Qlik AI Council was launched in January 2024 to provide continuous guidance and insight into the rapidly evolving AI landscape. Comprising distinguished experts in AI and ethics, the Council advises Qlik’s R&D and solutions teams, ensuring that AI innovations are both cutting-edge and ethically sound. By focusing on trustworthy, reliable, and minimally risky AI development, the Council aligns Qlik’s solutions with customer needs and broader societal impacts. Their expertise supports Qlik in delivering AI solutions that drive significant business outcomes while maintaining high levels of integrity.
The Council’s panel session at Qlik Connect 2024 delivered a critical message: data integrity is essential for successful AI adoption. Neglecting this can lead to severe operational, financial, and reputational issues. The Council members stressed that a focus on data and analytics foundations is vital for ethical AI development, public trust, sustainability, and innovative problem-solving. Businesses must prioritize data accuracy, diversity, security, and structure to harness AI’s full potential effectively.
