Value Realization for enterprises with AI based contract analysis

Enterprises are losing millions of dollars due to flawed and inefficient contract analysis processes, resulting in revenue leakage, non-compliance, higher cost of operations etc. This is particularly true for those who have adopted a traditional approach to contract analysis by leveraging a team of lawyers or supplementing them with template or rule-based software to semi-automate the process. Such approaches have gaping flaws such as inflexibility, inaccuracy, inability to learn from reviewer-corrections, being non-scalable and more. To know more about such challenges, I would urge you to read my earlier blog . In that blog, it is recommended to switch to an effective Artificial Intelligence (AI) based contract analysis tool, which can progressively learn, adapt, accurately predict and extract the key elements of the contract, mitigate risks and more. This blog focuses on how AI Enabled XtractEdge Contract Analysis business solution can help enterprises realize value in their contract-analysis journey.

XtractEdge Contract Analysis

XtractEdge Contract Analysis is an AI enabled business solution, built on XtractEdge, which leverages Machine learning (ML), Semantic Modelling and Deep Learning to automate and transform the process of analysing and reviewing contracts. This application identifies pre-defined legal clauses in contracts, determines contentious clauses, and scores each contract clause for risk in the given context. A front-end conversational interface allows end-users to infer, search, query, and reason with the model using natural language. It uses parallel neural pathways with text and vision-based learning to enhance model prediction.

XtractEdge Contract Analysis Key Capabilities

How XtractEdge Contract Analysis is helping enterprises in their contract analysis journey

XtractEdge Contract Analysis has been helping organizations realize significant business values in their contract analysis and review journey, through improved compliance rates, prevention of losses, reduced cost of operations, risk mitigation, elimination of contracts’ inefficiencies, improved staff productivity and employee satisfaction. Some of the actual examples are as follows:

There are many more success stories on how XtractEdge Contract Analysis has been helping enterprises in their contract analysis journey. Its well-defined yet flexible roadmap, and periodic releases signify that its new upcoming features will continue to help enterprises in their value realization and stay ahead of the curve.

Artificial Intelligence in Sports – A Smarter Path to Victory

Artificial intelligence (AI) is revolutionizing sports and elevating it to a whole new level. While it is true that statistics and quantitative analysis have played a central role in sports for a long time, AI is significantly impacting the way the game is strategized, played and engaging the audience. We see this trend pervading across Baseball, Tennis, Soccer, Football, Basketball and many others.

The 4 ways AI will continue to impact sports currently and transform it into the near future are – enhancing player performance, strategy & coaching, fan engagement & experience, transforming media & broadcasting.

AI has penetrated the locker room discussions with way better insights about the competition, the coach’s advice with better trends and your TV screens with faster highlights. That’s not all. AI is paving a smarter path to victory in sports for everyone from sportspersons to broadcasters, with real time game statistics for players and fans, game tactics prediction to enable the player to choose the right strategy and even alert the player in case of a potential decline in performance or injury. Technology has become pervasive in sports and a key contributor to its evolution both inside the stadium and outside enabling each player and team to be the best of themselves.

Player Performance and Potential

A combination of sensor technology and AI, helps coaches improve players’ technique. For example, in weight training – now virtually universal across sports – AI can provide real-time feedback to maximize the results of a workout and create personalized training regimens that busy coaches may not be able to provide. Wearables can also provide data around levels of strain and exertion, a player is experiencing and can signal that an activity should be stopped in order to prevent injury. This is particularly important at the high school level.

Coaching the Coaches

AI is having a major impact on strategic decisions coaches make, both before and during a game. Baseball is a classic example. Decisions about what line-up to field against opposing teams are now influenced as much by computer analysis from the front office as by the experience of the manager. Through a combination of wearable sensors and high speed cameras, AI platforms can now measure the speed, spin and placement of a tennis serve, a curve ball, a forward pass, a penalty kick and dozens of other similar actions, not to mention the motions and positioning in space of the players who perform them. All this data makes coaches better able to prepare players for competition. Equally important, AI can predict the chances of success for various game tactics. For example, some football coaches are now turning to AI to help them call the right plays during a game.

AI will surely become more and more important in the area of recruitment for college athletes and player selection in professional sports. Machine learning can find relationships that are not obvious but might play a significant role in a player’s contribution to a team. Sports teams, particularly at the professional level, are extremely competitive and will look for any possible edge, and that includes listening to what computers may have to say.

Enriching the Experience

AI can now deliver advanced performance analytics, whether it’s finding clips of all the winning tactics or visual analysis of every play. This gives players and coaches a powerful tool to analyze how they performed, and explore their opponent’s strengths and weaknesses. For example, in the upcoming Roland-Garros, Infosys has partnered to develop Stats+, which re-orders the statistics in a live match based on its individual influence on the outcome of the match. This point by point, dynamic and live feature is based on the principles of AI/ML to enrich fan and player experience.

Automating the Media

With the help of AI platforms, the cameras that now capture sporting events are also able to pick out the highlights of a game for distribution to television outlets or mobile devices. AI-based capabilities now extend to print as well. A natural language platform has been developed that transforms raw data from minor league baseball games into readable stories. With this capability, the Associated Press news service has increased its reporting capability and is now able to cover 13 minor leagues with 142 teams via AI.

At the Australian Open in 2019, AI Clips enabled a new wave of story-telling for AO’s media teams. AI Clips stitched together match data & video data and leveraged advanced analytical capabilities to create and automate rapid highlight packages. The snack-able content was generated in real-time with minimal human intervention, in a matter of seconds and with120 + different filters and 1000 combinations to choose from, creating an unparalleled viewing experience. Eventually, these power videos were consumed by fans across the world on Facebook, Twitter and other official online AO platforms.

The Future of Sports

AI in sports is here to stay, and as the technology improves through better sensors, processors and algorithms, it will become even more important. Whether through an internal IT organization or via external AI platforms, sports organizations now need AI to successfully compete at the highest levels.

Struggling with your traditional contract analysis processes? Switch to AI

Does the review and analysis process of your contracts cause delays in your business operations? Are your legal experts spending a significant portion of their time on repetitive manual work related to contracts review? Then, you are not the only one. Today, contract analysis has become a nightmare for many organizations. Some of them have been approaching contract analysis manually through a team of lawyers. Others have adopted a semi-automatic approach of supplementing their legal workforce with their home-grown software programs or leveraging a third-party software tool to assist. Most of these traditional solutions to address the underlying challenges have proved to be ineffective and inhibit business agility.

Current Challenges

Enterprises are grappling with a multitude of challenges pertaining to contract analysis and review. Some of these are as follows:

What is the solution to this nightmare?

Leveraging only lawyers in contract analysis is clearly time consuming, expensive, error-prone and not scalable. Traditional software tools have attempted to automate or semi-automate contract analysis by using templates, rules and conventional programming techniques. They suffer from limitations such as low accuracy, not being adaptable to handle bespoke contracts, inability to learn from reviewer corrections, inability to accurately extract from complex tables, inability to cope with surging volumes and more.

What we need is an effective Artificial Intelligence (AI) based contract analysis tool, which can be trained quickly to subsequently automate extraction of the contract elements, learn from reviewer corrections, scale dynamically and more. To learn more about how enterprises can realize value out of AI based contract analysis tools, keep watching this space.

Transforming Enterprise RPA Strategy with Analytics

“If you can’t measure it, you can’t improve it.”

Robotic Process Automation (RPA), an innovative form of business process automation technology that was introduced in 2000, has witnessed immense adoption in past few years. As per a recent survey conducted, 53% enterprises have already started their RPA journey and this is expected to increase to 72%1.

The benefits of RPA adoption are significant and it is no surprise that RPA has become a buzzword in technology space, drawing a lot of interest from industry and investors. With the payback reported in less than 12 months, enterprises have observed improvement in compliance (92%), higher quality / accuracy (90%), enhanced productivity (86%) and reduction in cost (59%)2. While RPA is brimming with potential, a recent research by EY claims that 30-50% of the RPA implementations have failed3 in generating desired outcomes, leading to questions on RPA capabilities. It has also been observed that many CIOs have stalled their ongoing process automations to revisit their decision.

What drove CIOs to significantly invest onto untested and unexplored technology? The untapped potential of RPA to drive valuable business results in terms of higher accuracy and productivity were of course attractive and considered. The limitations of a RPA solution were probably ignored. To measure the results of a solution, it is essential to know the success metrics and this critical parameter was unfortunately set by very few enterprises before selecting a process for RPA adoption. Investing without the possibility to measure benefits is an absolute risk.

This is where RPA Analytics comes in and becomes an integral part of Automation Implementation journey. Integration of analytics with RPA, i.e. the information resulting from the systematic analysis of data and statistics, has now made such investment decisions more informed and calculated. Analytics in RPA can be applied in 3 stages:

So, when should an organization seek analytics in RPA? The pre-requisite for analytics is the data generated for a process. To enhance the value of RPA, quality data must be analyzed using the RPA adoption tools at the right intervals. Analytics will help firms shortlist the right use cases and decide whether to proceed with RPA.

Analytics will not just bolster the enterprise RPA strategy, but also ensure a successful adoption of the latest technology.

References:

1, 2 – https://www2.deloitte.com/bg/en/pages/technology/articles/deloitte-global-rpa-survey-2018.html

3 – https://www.ey.com/Publication/vwLUAssets/Get_ready_for_robots/$FILE/ey-get-ready-for-robots.pdf

The 7 commandments of assuring a successful automation journey

Introduction

While organizations from all parts of the world seem to be smitten by the benefits of Robotic Process Automation (RPA), surprisingly, only a few have succeeded at harnessing it to their advantage. As per a Forrester report, the RPA market is expected to grow to $2.9 billion in 2021. The market was valued at only $250 million in 2016. Many research firms anticipate that the RPA market will grow at a CAGR of over 36% and that the market size would cross $8 billion by 2023!

By automating recurring costs, enterprises have experienced more productivity, enhanced efficiency at lowered costs. Although automation has become an everyday term, the results indicate that not everyone has tasted success with it. If automation is slated to be the next best thing, with enterprises across the world vouching for its impact on their businesses and economy, why is it that we are yet to realise the full benefit of automation? Why is it that only a few have been able to make the most out of it?

Why do automations fail?

Automation is that one word, which always creates excitement amongst business leaders, CIOs and the likes. Though, it has become a buzz word in leadership communications and strategic meetings, little have the industries experienced in terms of automation success and ROI. Getting processes automated and doing so successfully are two very different things.

Though vendors and service providers lure customers by calling their RPA solutions as easy to implement and maintain, it is easier said than done. As per a recent report by KPMG and HFS Research, there’s a significant gap between expectations and reality in the RPA space. While enterprises understand the benefits of RPA, the study found that many are not yet ready to implement it effectively, with only 13% of enterprise RPA initiatives achieving scale across the entire organisation, according to their survey.

While automation has become imperative to stay relevant in the market today, it would yield results, only when processes are automated the way they should be. Currently, enterprises are approaching automation as a short-term plan, without aligning people and implementing effective change management. Effective roll-out of RPA calls for adhering to certain practices, which ensure smooth implementation and success.

So, what does it take to taste success with automation?

 As automation is known to significantly improve business response time, efficiency, accuracy and reduce man hours spent on time-taking repetitive tasks, organizations may want to automate every process. But it is advisable to plan it better and make the best use of time and resources needed to implement automation. As many organizations move to build their automation capabilities, there are certain best practices that help differentiate successful efforts from others.

Here are some of the best practices that could help you realise success in your automation plan.

Conclusion

There are various factors that lead to the success of an automation process and each one must be taken into account when automating processes in an organization. If done without contemplating the good and bad, it would not provide the desired outcome. The above given seven commandments are the best practices to reap the benefits of your investment. Follow these best practices and assure automation success for your organization.

References:

https://www.hfsresearch.com/pointsofview/rpas-ticking-time-bomb-enterprises-and-service-providers-must-make-rpa-talent-their-top-priority-to-avoid-disaster

https://financesonline.com/8-best-practices-in-business-process-automation-bridge-gap/

http://www.doclogix.com/six-steps-towards-successful-automation-company-processes/

https://automationedge.com/ten-tips-successful-automation/

https://www.mitratech.com/resource-hub/blog/thinksmart-insider-tips-successful-automation-project/

https://www.mckinsey.com/business-functions/operations/our-insights/the-automation-imperative