Given the responsibility of understanding 181,000 laws, approximately 159 legal systems, up to 100 million pending cases, and countless case records, a career as a Brazilian litigation lawyer is not for the dim of heart.
When attorney Karla Capela Morais and her colleagues struggled with case management, she knew there had to be a better way. She believed technology could lend a hand solve the enormous challenges of tracking individual cases and timelines, managing volumes of unstructured data, and identifying precedents and trends. Morais leveraged her experience and passion for the law to design a case management solution that leverages artificial intelligence, machine learning, and natural language processing. In 2016, she founded the legal services provider KOY Inteligência Jurídica (KOY).
KOY, like many people who are navigating the path to AI adoption and integration, finds that it’s not necessarily effortless. Travelers are often forced to navigate data holes and pitfalls – too much, too little, non-standard formats or unknown origins. In a study commissioned by IBM titled Overcome Obstacles To Get To AI At Scale Forrester Consulting reports that companies consider AI initiatives a top priority in digital transformation and a driver of critical business outcomes; however, ineffective and unruly data, combined with talent shortages and a lack of trust in AI, make adoption much more tough. In fact, 90% of survey respondents admit that scaling AI is tough. The main challenges are data quality and governance. Forrester found that 58% of respondents lack data quality and 40% struggle with data management issues.
In a panel conversation with Karla Capela Morais, CEO and Founder of KOY, moderated by Srividya Sridharan, Vice President and Chief Research Officer at Forrester, we discussed the importance of data management and governance to the success of a law firm’s AI environments.
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We all agreed that regardless of size, location or regulatory environment, data is the lifeblood of organizations. Expertly collected and effectively managed data provides a solid basis for artificial intelligence. Without this foundation, data quality issues and governance issues can interrupt the AI journey, ultimately impact the customer experience, hinder innovation, and cause unnecessary costs and delays. Properly preparing data for the needs of artificial intelligence is a key, fundamental step towards reaping the benefits of artificial intelligence.
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If you’re embarking on an AI initiative, you most likely have a data problem – perhaps several. For a significant number of organizations, the time-honored ways companies manage data do not work well with the novel way of analyzing data through AI and analytics,” said Srividya Sridharan, vice president and chief research officer at Forrester, during our panel discussion. “The data collection and management systems that previously supported your organization’s operations, customer service, financial planning and strategic initiatives may not work for your AI initiatives.” Why? Many data stores were not designed for employ in artificial intelligence. If you are in this situation, you are not alone. Forrester research found that 52% are not confident in their ability to effectively employ data for AI.
Start petite and then grow your AI solution
Morais compares artificial intelligence to mathematical logic. If you have bad data, your conclusions and observations will be wrong. “In Brazil, we do not have structured data sources for lawsuits. We needed robust natural language processing capabilities,” he says. “When we implemented AI, our first technology challenge was unifying our data and creating consistent definitions for use across all data sources.” The need for a structured data definition is not confined to start-up organizations.
There is a saying in Brazil: “done is better than perfect.” Even if you don’t have the best data, get it together to start and then continue to improve it,” says Morais.
KOY used IBM Watson® Natural Language Processing technology to process volumes of unstructured data. IBM Watson Natural Language Understanding analyzes downloaded text to extract metadata from content. Concepts, entities, keywords, categories, moods, emotions and semantic roles are deciphered to enhance language understanding. With the database in place, KOY developed an AI platform that provides case management services to its clients.
Trusted AI tools deliver better results
Using IBM Watson Machine Learning and IBM watsonx Assistant technology, Norma constantly learns at incredible speeds based on novel information regarding issues entered into the KOY AI system and customer inquiries. Where it takes one lawyer two hours to read a lawsuit, Norma reads it in six seconds.
There is a persistent belief that artificial intelligence competes with humans. Morais disagrees. “Those who work with artificial intelligence will achieve exponentially better results,” he says. “When integrated, trusted data is the foundation, your team gains new and better insights. This puts us in a very strategic position in the industry.”
Standard provides automated wise schedule processing, managing thousands of schedules for KOY customers simultaneously. It helps you prioritize cases and optimize process flow by notifying lawyers of upcoming deadlines and relevant information regarding their lawsuit volume. Case management and planning are crucial to the Brazilian legal community as statutes of limitations for cases can be up to ten years. Norma also helps its clients monitor and reconcile settlements and disbursements throughout the life of their cases. With Norma’s lend a hand, KOY customers achieve increased productivity and revenue.
Learn about the DataOps strategy (data operations).
How can organizations map the process to meet their AI needs? IBM recommends tracking your organization’s bottlenecks back to the data source. A repeatable process — known as data operations (DataOps) — can lend a hand organizations eliminate bottlenecks, especially those related to data that was never designed or built for AI. IBM DataOps coordinates people, processes and technology to quickly deliver reliable, high-quality data to the data citizen. This practice helps enable collaboration across the organization to enable agility, speed, and novel data initiatives at scale.
The most critical thing to remember is that you and your organization are not alone. KOY’s success story illustrates one customer’s invigorating AI journey. Other paths may better suit your organization’s needs. To learn insights from other leaders on the AI journey, read Forrester’s study: Overcome the hurdles to access AI at scale and start your journey today.
Find out how artificial intelligence can maximize your competitive advantage.