AI toolkit and best practices from LexisNexis helps future-proof AI projects
The ‘Credible AI Strategy Toolkit’, developed by LexisNexis, is a proven solution for ensuring AI adoption within organisations aligns with ethical and regulatory standards.
Today’s regulatory landscape leaves little room for companies with AI strategies that are not completely credible. That means firms – including consultancies – need to ensure the integrity of their data. The ‘Credible AI Strategy Toolkit’ offers a solution for future-proofing AI strategies.
From machine learning to predictive analytics, and from natural language processing to GenAI (generative AI), new technologies are revolutionising various aspects of business and society. Yet the reality is that the vast majority of corporate AI and big data projects fail – as high as 80%, according to Harvard Business Review.
“The world of work stands at a compelling crossroads, with generative AI set to play a pivotal role in its future evolution,” said Snehit Cherian, chief technology officer at Nexis Solutions.
Leveraging the opportunities of AI (and GenAI in particular) is high on the list of CEOs in a range of industries. Underpinning the rise of AI is the need for high-quality, accurate, and trustworthy data to power the technology.
Data quality management
Companies need to ensure that their data is comprehensive, that their sources and reliable, and that they can demonstrate where their data comes from, LexisNexis stresses. AI’s insights are most valuable when they are based on a wide range of datasets, when the data is credible and accurate, and if sources are available in order to mitigate the risk of AI ‘hallucinations’.
Other aspects that need to be taken into consideration: Where the data was collected, how it can be used, whether it is compliant with intellectual property and data privacy rules, and how ethical standards are kept.
While early adopters of AI may have briefly boasted a competitive advantage, some companies that moved too fast have allegedly used data that is at best inaccurate and from bad sources, and at worst unethically or illegally acquired.
Some major firms tech companies are facing lawsuits over issues like scraping the internet, including personal social media accounts. Other companies have brought in new tech that has built-in ‘algorithmic bias’, or in other words, a bias in the way the tech works that disadvantaged certain groups of people.
“Anxiety over job displacement due to automation, AI hallucinations, data privacy issues, and even ethical questions about algorithmic bias and decision-making transparency have created skepticism,” said Cherian.
Better data means better outputs
Data for AI is becoming increasingly valuable to all kinds of organisations. Companies are finding that AI powered by low-quality data brings new risks for them to manage. While an ethical approach to AI, which leverages credible data, offers them a competitive advantage and fosters trust in their use of technology.
According to LexisNexis, nearly 90% of respondents to a survey said the quality and accuracy of GenAI’s output will be the main consideration in their use of the tool. Nearly 75% of executives said better transparency and explanation of decision-making about GenAI use will foster more trust.
AI best practices
To maximise the value of AI and big data initiatives, organisations must focus on robust data foundations, clear strategy, and ethical compliance. LexisNexis lays out these AI best practices:
Acquire comprehensive data
Seek a wide range of datasets, including news, legal, company, financial, and social media data.
Assure data accuracy and quality
More data is not always better if it is inaccurate or outdated. Understand data provenance and use a trusted provider.
Invest in the best technology
Constant investment is required to keep up with new trends and tools like GenAI, potentially requiring new staff or third-party expertise.
Fuel technology with optimised data
Use datasets enriched by data scientists to accelerate time-to-insight. Data should be clean, consistent, and compatible, like Nexis Data+’s industry-standard JSON responses.
Lead from the top on data and tech
The C-Suite must set and communicate the direction for AI and big data objectives to foster a positive data culture and prevent silos.
Start from the business strategy
Align AI use with your firm’s core strategic objectives and challenges. A data strategy is critical for deriving value from GenAI.
Consider ethical issues
Understand regulations around data protection, privacy, and cybersecurity. Address issues like algorithmic bias and ensure a staff member reviews AI outputs before action is taken.
Unlocking GenAI’s potential
The bottom line: A company’s best chance of successfully embracing the opportunities of AI is to use only the highest-quality, enriched data which is sourced in a legally and ethically compliant manner and delivered through a flexible API.
“We believe that through collaboration and a shared understanding of GenAI, organisations can adopt and embrace the massive opportunities it provides which is why this is exactly what we are focused on at LexisNexis,” said Todd Larsen, president of Nexis Solutions.
