Icertis, the contract intelligence company pushing the boundaries of what's possible with Contract Lifecycle Management (CLM), today announced its inclusion in the Financial Times (FT) list of 2023 Americas' Fastest Growing Companies. Based on its revenue growth rate, Icertis ranks 239th on the prestigious list of 500 companies in 20 countries across the Americas. "Icertis surpassed $200 million in annual recurring revenue in 2022 and grew over 40% year-on-year, and we are uniquely positioned to transform the foundation of commerce through contracts while maintaining a consistent and lasting." Building companies," said Samir Bodas, Chairman and CEO of Icertis. "By applying artificial intelligence to contract data, Icertis established Contracts as the fifth system of record, capturing a company's entitlements and obligations for all of its customers, partners, suppliers, and employees.

Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Traditional contract lifecycle management (CLM) tools focus on improving document workflows. However, Icertis seeks to take the field to the next level with contract intelligence that uses artificial intelligence (AI) and machine learning (ML) to automatically extract contract data at scale. These tools are designed to structure contracts' commercial, legal and operational data and connect that data to procurement, ERP and human capital management apps to help companies accelerate revenue, reduce costs, improve risk management and ensure compliance. When VentureBeat previously covered Icertis in 2019, the CLM market was expected to be worth $3.16 billion by 2023.

"Contracts are the foundation of commerce." Does this sound like an overstatement? When you think about almost any ongoing business transaction (be it with a supplier, a customer, a partner or an employee), there is most likely a contract that defines the terms of the relationship--the obligations, the entitlements, the dollars in and dollars out. Amazingly, the written word itself seems to have been invented to record contracts. According to a recent exhibit at the British Library, cuneiform script has been traced back to traders in Mesopotamia whose commercial agreements became too complex to commit to memory. However, in today's fast, digital-first business environment, the critical data found in contracts is left out of the operational systems of record that companies run on.

Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research. Volkswagen Financial Services (VWFS), as a market leader in vehicle leasing services, aims to leverage existing proprietary data and the latest research to enhance existing and derive new business processes. The collaboration between Information Systems and Machine Learning Lab (ISMLL) and VWFS serves to realize this goal. In this paper, we propose methods in the fields of recommender systems, object detection, and forecasting that enable data-driven decisions for the vehicle life-cycle at VWFS.

Contracting is a common activity, but it is one that few companies do efficiently or effectively. In fact, it has been estimated that inefficient contracting causes firms to lose between 5% to 40% of value on a given deal, depending on circumstances. But recent technological developments like artificial intelligence (AI) are now helping companies overcome many of the challenges to contracting. The main challenge firms face in contracting arises from the sheer number of contracts they must keep track of; these often lack uniformity and are difficult to organize, manage, and update. Most firms don't have a database of all the information in their contracts – let alone an efficient way to extract all that data – so there's no orderly and fast way to, for example, view complex outsourcing agreements or see how a certain clause is worded across different divisions.

Contracting is a common activity, but it is one that few companies do efficiently or effectively. In fact, it has been estimated that inefficient contracting causes firms to lose between 5% to 40% of value on a given deal, depending on circumstances. But recent technological developments like artificial intelligence (AI) are now helping companies overcome many of the challenges to contracting. The main challenge firms face in contracting arises from the sheer number of contracts they must keep track of; these often lack uniformity and are difficult to organize, manage, and update. Most firms don't have a database of all the information in their contracts – let alone an efficient way to extract all that data – so there's no orderly and fast way to, for example, view complex outsourcing agreements or see how a certain clause is worded across different divisions.

We encounter stories and predictions about how artificial intelligence (AI) will fundamentally change a variety of industries on an almost day-to-day basis. In fact, it has become such an important topic that late last year the Council for Society and Technology wrote a letter to the Prime Minister advising how the UK could take advantage of opportunities created by the increasing convergence of robotics, automation and artificial intelligence. As more and more industries, including healthcare and financial services, adopt AI technology, we'll continue to see increased benefits on our society as a whole. Conversations about AI tend to have a sci-fi vibe: robot personal assistants, self-driving cars, you name it. But the real, day-to-day business value of AI is much less futuristic, starting with the hundreds and thousands of contracts that keep business deals up and running every day.

Autonomy and artificial intelligence may be integral to the Defense Department's Third Offset Strategy, but making those technologies useful will require IT investments to integrate them into defense systems, a new report says. "Both the DOD and the Intelligence Community, they are investing in these technologies. So artificial intelligence is a big priority area, machine learning, all these technologies," Matthew Hummer, director of analytics at big-data and analytics firm Govini, told FedScoop. "But they haven't really done a good job of integrating it into the current Distributed Common Ground Systems. And that's because those systems really need pretty much a big overhaul to be able to do that."