ne of the characteristics of the workplace of 2020 has been the lack of people in the office. COVID-19 saw a significant proportion of businesses adopt remote work in support of efforts to contain the pandemic.

Is there a better way, a smart way for businesses to organise their workforce so that they can optimise fixed assets like facilities?

Jones Lang LaSalle (JLL) forecasts that “upwards of 40% of today’s office assets need some form of enhancement to stay relevant.” The JLL report, Home and away: the new workplace hybrid?, suggests that during the COVID-19 period, 68% of employees were working from home.

FutureCIO spoke to Dinesh Malkani, founder and CEO of Smarten Spaces, how COVID-19 is forcing organisations to reimagine the workplace.

Smarten Spaces has built technology and platform to make smarter and better use of workspaces. Malkani acknowledged that technology penetration in space management remains low although the pandemic may be changing that.

“Every office is being re-done as people are moving towards the hybrid workplace. We happen to be a startup that has the entire technology solution ready to bring companies to hybrid working in the hybrid workplace.”

Dinesh Malkani

Sundar Nagarajan, head of Consulting at JLL, noted that the pace of digitization and adoption of automation in 2020 has accelerated businesses to 2023-2024 levels right away, adjusting decision-making and way of working – all in the name of revenue.

Malkani noted that the shift to a hybrid model of work is not entirely driven by COVID-19. Organisations have been studying this opportunity even before that. He did acknowledge that many such discussions floated around experimentations. He credits the pandemic as proving that it is possible to sanction work from anywhere without sacrificing productivity or risking security.

“Companies have been moving in the direction of being able to work from anywhere – in the office, co-working space, or home, in what we now classify as hybrid work strategies,” he concluded.

Challenges for leadership

According to Malkani, the challenge for CHROs is to ensure that they’re able to offer the notion of flexibility to all of the workforce. “They will then need to consider the policies and rules around such arrangements. HR teams today are grappling with the fact that we can now hire anyone from anywhere in the world, as we work remotely,” he added.

For CFOs and CEOs, the discussion will become mainly about cost considerations and the optimum use of whatever approach is taken by the company. The CIO’s task will be around the use of technology to facilitate hybrid work strategies.

Technology-led adoption

“To create a frictionless environment where workforce productivity is at its peak, a lot of data needs to be relooked at. The CIO will need to ensure that the environment and network are secure and that regulations are complied with,” he added.

According to Malkani, the pandemic has influenced what and how technology is being used in the workplace. Employee safety and the ability to find available space have become important considerations in the adoption.

“Incorporating technology is key in making it easy and essential for the user to address their concerns, and that’s when the adoption rate becomes high. Technology is no longer a nice to have. Beyond providing data, AI-incorporated technology that provides recommendations to business owners has a huge role to play in driving adoption rates,” he added.

He saw the shift to AI within the realm of workspaces as an essential ingredient to achieving a successful hybrid workplace that is very productive and cost-effective.

Click on the podchat player above to listen to Malkani share his opinion and recommendations on the better use of workspaces using technology.

  1. How do you see space-as-a-service and office decentralization changing the workplace of the future?
  2. But how do you see space-as-a-service and office decentralisation changing the workplace of the future?
  3. Analysts suggest that the post-COVID workplace normalisation will combine remote work together with the traditional office environment. How will this shift impact the way CIOs, CEOs, CHROs and CFOs these executives do their job?
  4. How does the CIO ensure that they are able to connect or to manage the workforce and the facilities that they use including network infrastructure, the applications, even when those persons are not in the actual enterprise facility, the operations itself?
  5. How do technologies like those of Smarten Spaces protect data privacy?
  6. What is the Smarten Space value proposition for mall operators?
  7. What will further drive the adoption of technologies, similar to what Smarten Spaces offers today?
  8. When you pitch a Smarten Spaces solution to prospective clients, what’s the typical objection that they would present to you?
  9. What do you see in terms of emerging technologies that will further influence the proptech market that you are in?

 


Artificial intelligence is one of the hottest buzzwords in legal technology today, but many people still don’t fully understand what it is and how it can impact their day-to-day legal work.

According to  Brookings Institution, artificial intelligence generally refers to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment, and intention.” In other words, artificial intelligence is technology capable of making decisions that generally require a human level of expertise. It helps people anticipate problems or deal with issues as they come up. (For example, here’s how artificial intelligence greatly improves contract review.)

Recently, we sat down with Onit’s Vice President of Product Management, technology expert and patent holder Eric Robertson to cover the ins and outs of artificial intelligence in more detail. In this first installment of our new blog series, we’ll discuss what it is and its three main hallmarks.

Podcast alert: Hear Eric discuss artificial intelligence in more detail by listening to the podcast below.

What Is Artificial Intelligence?

At the core of artificial intelligence and machine learning are algorithms, or sequences of instructions that solve specific problems. In machine learning, the learning algorithms create the rules for the software, instead of computer programmers inputting them, as is the case with more traditional forms of technology. Artificial intelligence can learn from new data without additional step-by-step instructions.

This independence is crucial to our ability to use computers for new, more complex tasks that exceed the manual programming limitations – things like photo recognition apps for the visually impaired or translating pictures into speech. Even things we now take for granted, like Alexa and Siri, are prime examples of artificial intelligence technology that once seemed impossible. We already encounter in our day-to-day lives in numerous ways and that influence will continue to grow.

The excitement about this quickly evolving technology is understandable, mainly due to its impacts on data availability, computing power and innovation. The billions of devices connected to the internet generate large amounts of data and lower the cost of mass data storage. Machine learning can use all this data to train learning algorithms and accelerate the development of new rules for performing increasingly complex tasks. Furthermore, we can now process enormous amounts of data around machine learning. All of this is driving innovation, which has recently become a rallying cry among savvy legal departments worldwide. 

Once you understand the basics of artificial intelligence, it’s also helpful to be familiar with the different types of learning that make it up.

The first is supervised learning, where a learning algorithm is given labeled data in order to generate a desired output. For example, if the software is given a picture of dogs labeled “dogs,” the algorithm will identify rules to classify pictures of dogs in the future.

The second is unsupervised learning, where the data input is unlabeled and the algorithm is asked to identify patterns on its own. A typical instance of unsupervised learning is when the algorithm behind an eCommerce site identifies similar items often bought by a consumer.

Finally, there’s the scenario where the algorithm interacts with a dynamic environment that provides both positive feedback (rewards) and negative feedback. An example of this would be a self-driving car where, if the driver stays within the lane, the software will receive points in order to reinforce that learning and reminders to stay in that lane.

The Hallmarks of AI

Even after understanding the basic elements and learning models of artificial intelligence, the question often arises as to what the real essence of artificial intelligence is. The Brookings Institution boils the answer down to three main qualities:

  1. Intentionality – Artificial intelligence algorithms are designed to make decisions. They’re not passive machines capable only of mechanical or predetermined responses. Rather, they’re designed by humans with intentionality to reach conclusions based on instant analysis.
  2. Intelligence – Artificial intelligence often is undertaken in conjunction with machine learning and data analytics, and the resulting combination enables intelligent decision-making. Machine learning takes data and looks for underlying trends. If it spots something relevant for a practical problem, software designers can take that knowledge and employ data analytics to understand specific issues.
  3. Adaptability – Artificial intelligence has the ability to learn and adapt as it compiles information and makes decisions. Effective artificial intelligence must adjust as circumstances or conditions shift. This could involve changes in financial situations, road conditions, environmental considerations, military circumstances, and more. Artificial intelligence needs to integrate these changes into its algorithms and decide on how to adapt to the new circumstances.

For a more in-depth discussion of artificial intelligence, you can listen to the entire podcast interview with Eric here.

 


ne of the characteristics of the workplace of 2020 has been the lack of people in the office. COVID-19 saw a significant proportion of businesses adopt remote work in support of efforts to contain the pandemic.

Is there a better way, a smart way for businesses to organise their workforce so that they can optimise fixed assets like facilities?

Jones Lang LaSalle (JLL) forecasts that “upwards of 40% of today’s office assets need some form of enhancement to stay relevant.” The JLL report, Home and away: the new workplace hybrid?, suggests that during the COVID-19 period, 68% of employees were working from home.

FutureCIO spoke to Dinesh Malkani, founder and CEO of Smarten Spaces, how COVID-19 is forcing organisations to reimagine the workplace.

Smarten Spaces has built technology and platform to make smarter and better use of workspaces. Malkani acknowledged that technology penetration in space management remains low although the pandemic may be changing that.

“Every office is being re-done as people are moving towards the hybrid workplace. We happen to be a startup that has the entire technology solution ready to bring companies to hybrid working in the hybrid workplace.”

Dinesh Malkani

Sundar Nagarajan, head of Consulting at JLL, noted that the pace of digitization and adoption of automation in 2020 has accelerated businesses to 2023-2024 levels right away, adjusting decision-making and way of working – all in the name of revenue.

Malkani noted that the shift to a hybrid model of work is not entirely driven by COVID-19. Organisations have been studying this opportunity even before that. He did acknowledge that many such discussions floated around experimentations. He credits the pandemic as proving that it is possible to sanction work from anywhere without sacrificing productivity or risking security.

“Companies have been moving in the direction of being able to work from anywhere – in the office, co-working space, or home, in what we now classify as hybrid work strategies,” he concluded.

Challenges for leadership

According to Malkani, the challenge for CHROs is to ensure that they’re able to offer the notion of flexibility to all of the workforce. “They will then need to consider the policies and rules around such arrangements. HR teams today are grappling with the fact that we can now hire anyone from anywhere in the world, as we work remotely,” he added.

For CFOs and CEOs, the discussion will become mainly about cost considerations and the optimum use of whatever approach is taken by the company. The CIO’s task will be around the use of technology to facilitate hybrid work strategies.

Technology-led adoption

“To create a frictionless environment where workforce productivity is at its peak, a lot of data needs to be relooked at. The CIO will need to ensure that the environment and network are secure and that regulations are complied with,” he added.

According to Malkani, the pandemic has influenced what and how technology is being used in the workplace. Employee safety and the ability to find available space have become important considerations in the adoption.

“Incorporating technology is key in making it easy and essential for the user to address their concerns, and that’s when the adoption rate becomes high. Technology is no longer a nice to have. Beyond providing data, AI-incorporated technology that provides recommendations to business owners has a huge role to play in driving adoption rates,” he added.

He saw the shift to AI within the realm of workspaces as an essential ingredient to achieving a successful hybrid workplace that is very productive and cost-effective.

Click on the podchat player above to listen to Malkani share his opinion and recommendations on the better use of workspaces using technology.

  1. How do you see space-as-a-service and office decentralization changing the workplace of the future?
  2. But how do you see space-as-a-service and office decentralisation changing the workplace of the future?
  3. Analysts suggest that the post-COVID workplace normalisation will combine remote work together with the traditional office environment. How will this shift impact the way CIOs, CEOs, CHROs and CFOs these executives do their job?
  4. How does the CIO ensure that they are able to connect or to manage the workforce and the facilities that they use including network infrastructure, the applications, even when those persons are not in the actual enterprise facility, the operations itself?
  5. How do technologies like those of Smarten Spaces protect data privacy?
  6. What is the Smarten Space value proposition for mall operators?
  7. What will further drive the adoption of technologies, similar to what Smarten Spaces offers today?
  8. When you pitch a Smarten Spaces solution to prospective clients, what’s the typical objection that they would present to you?
  9. What do you see in terms of emerging technologies that will further influence the proptech market that you are in?

 


Artificial intelligence is one of the hottest buzzwords in legal technology today, but many people still don’t fully understand what it is and how it can impact their day-to-day legal work.

According to  Brookings Institution, artificial intelligence generally refers to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment, and intention.” In other words, artificial intelligence is technology capable of making decisions that generally require a human level of expertise. It helps people anticipate problems or deal with issues as they come up. (For example, here’s how artificial intelligence greatly improves contract review.)

Recently, we sat down with Onit’s Vice President of Product Management, technology expert and patent holder Eric Robertson to cover the ins and outs of artificial intelligence in more detail. In this first installment of our new blog series, we’ll discuss what it is and its three main hallmarks.

Podcast alert: Hear Eric discuss artificial intelligence in more detail by listening to the podcast below.

What Is Artificial Intelligence?

At the core of artificial intelligence and machine learning are algorithms, or sequences of instructions that solve specific problems. In machine learning, the learning algorithms create the rules for the software, instead of computer programmers inputting them, as is the case with more traditional forms of technology. Artificial intelligence can learn from new data without additional step-by-step instructions.

This independence is crucial to our ability to use computers for new, more complex tasks that exceed the manual programming limitations – things like photo recognition apps for the visually impaired or translating pictures into speech. Even things we now take for granted, like Alexa and Siri, are prime examples of artificial intelligence technology that once seemed impossible. We already encounter in our day-to-day lives in numerous ways and that influence will continue to grow.

The excitement about this quickly evolving technology is understandable, mainly due to its impacts on data availability, computing power and innovation. The billions of devices connected to the internet generate large amounts of data and lower the cost of mass data storage. Machine learning can use all this data to train learning algorithms and accelerate the development of new rules for performing increasingly complex tasks. Furthermore, we can now process enormous amounts of data around machine learning. All of this is driving innovation, which has recently become a rallying cry among savvy legal departments worldwide. 

Once you understand the basics of artificial intelligence, it’s also helpful to be familiar with the different types of learning that make it up.

The first is supervised learning, where a learning algorithm is given labeled data in order to generate a desired output. For example, if the software is given a picture of dogs labeled “dogs,” the algorithm will identify rules to classify pictures of dogs in the future.

The second is unsupervised learning, where the data input is unlabeled and the algorithm is asked to identify patterns on its own. A typical instance of unsupervised learning is when the algorithm behind an eCommerce site identifies similar items often bought by a consumer.

Finally, there’s the scenario where the algorithm interacts with a dynamic environment that provides both positive feedback (rewards) and negative feedback. An example of this would be a self-driving car where, if the driver stays within the lane, the software will receive points in order to reinforce that learning and reminders to stay in that lane.

The Hallmarks of AI

Even after understanding the basic elements and learning models of artificial intelligence, the question often arises as to what the real essence of artificial intelligence is. The Brookings Institution boils the answer down to three main qualities:

  1. Intentionality – Artificial intelligence algorithms are designed to make decisions. They’re not passive machines capable only of mechanical or predetermined responses. Rather, they’re designed by humans with intentionality to reach conclusions based on instant analysis.
  2. Intelligence – Artificial intelligence often is undertaken in conjunction with machine learning and data analytics, and the resulting combination enables intelligent decision-making. Machine learning takes data and looks for underlying trends. If it spots something relevant for a practical problem, software designers can take that knowledge and employ data analytics to understand specific issues.
  3. Adaptability – Artificial intelligence has the ability to learn and adapt as it compiles information and makes decisions. Effective artificial intelligence must adjust as circumstances or conditions shift. This could involve changes in financial situations, road conditions, environmental considerations, military circumstances, and more. Artificial intelligence needs to integrate these changes into its algorithms and decide on how to adapt to the new circumstances.

For a more in-depth discussion of artificial intelligence, you can listen to the entire podcast interview with Eric here.

 


The Essential Guide to Neural MT: Neural Machine Translation in e-Discovery and Litigation Podcast. Iconic’s Sales Director, Stephen Davis, shares some information about Neural Machine Translation in e-discovery and litigation without getting weighed down with technical details. Listen Now: https://iconictranslation.com/2019/10/the-essential-guide-to-neural-mt-4-neural-machine-translation-in-e-discovery-and-litigation-podcast/


At the end of 2019, we completed 16+ years of customer excellence developing enterprise portals and web applications on Microsoft .NET, SharePoint and Salesforce platform integrated with SuccessFactors, SAP, NetDocuments, iManage, Elite, Aderant, Handshake, Interaction, LexisNexis, Kony, Symphony, and many more enterprise platforms. Learn more about our services at Legaltech – LegalWeek New York, booth no. 227.
Legal101 is currently being used by several small to mid-sized law firms worldwide as their Firm Intranet. With Legal101 firms can deploy a fully responsive mobile-first intranet portal within a couple of weeks that accelerates employee productivity and draws more value of their investment in SharePoint & Office365.
Schedule demo with us to understand how firms are modernizing their workplace with Legal101. Learn more – klstinc.com/legal101
In 2019, we also launched two brand new solutions that can boost law firm productivity and address collaboration issues.
KLoBot is a DIY voice+text Chatbot & Virtual Assistant builder platform that can be used to build, configure, and deploy ‘no-code’ chatbots within minutes. KLoBot platform is robust, secure, and incredibly intelligent designed for business users to create chatbots and deploy easily on your favorite channels along with pre-built connectors for SharePoint, Service Now, NetDocuments, iManage, Twilio, and many more!
netDocShare is an innovative solution that allows view & edit of NetDocuments content within SharePoint or your favorite web application. netDocShare supports viewing and editing NetDocuments content stored in Cabinets, Workspace, Folders, ShareSpaces, NDThread or CollabSpaces. netDocShare is currently being used across several AMLAW firms and Legal departments worldwide.
Visit us at Booth 227 or write to us at marketing@klstinc.com to get in touch with our team.

In 2019, KLST launched an AI Chatbot Builder Platform, KLoBot. 

KLoBot is a DIY voice+text Chatbot & Virtual Assistant builder platform that can be used to build, configure, and deploy ‘no-code’ chatbots within minutes. KLoBot platform is robust, secure, and incredibly intelligent designed for business users to create chatbots and deploy easily on your favorite channels along with pre-built connectors for SharePoint, Service Now, NetDocuments, iManage, Twilio, and many more!

Meet us at Booth 227 to know more!


netDocShare – View and edit NetDocuments content securely in any web app

netDocShare is an innovative solution that allows view & edit of NetDocuments content within SharePoint or your favorite web application. netDocShare supports viewing and editing NetDocuments content stored in Cabinets, Workspace, Folders, ShareSpaces, NDThread or CollabSpaces. netDocShare is currently being used across several AMLAW firms and Legal departments worldwide.

About KLST
KL Software Technologies (“KLST”) was founded in 2003 with the vision of building mobile-first digital innovations that provide smooth, intuitive, and consistent user experience across smarter interfaces. With global delivery centers based out of USA and India, KLST software+services offerings are focused on Enterprise Collaboration & Content, Hybrid Mobility, Cloud, Artificial Intelligence, and Augmented Reality. Learn more about KLST services: www.klstinc.com/whyklstforlegal