Category Archives: Automation

SAN JOSE, Calif.--(BUSINESS WIRE)--Kanverse.ai, a Hyperautomation company, has announced the global launch of the Iolite release of its patent-pending AI-powered Intelligent Document Processing Product for Enterprise.

Iolite release introduces powerful new features to Kanverse AP invoice automation product for enterprises.

Iolite release also brings a new out-of-box COINS ERP (Enterprise Resource Planning) integration for construction management and real-estate companies.

Kanverse iolite release enhances the insurance document processing product with innovative features.

Kanverse IDP combines multiple AI (Artificial Intelligence) technologies with Optical Character Recognition (OCR) and Automation to provide an end-to-end product that digitizes document processing for enterprises from ingestion, classification, extraction, validation, approvals to filing. The entire process is powered by Computer vision, Natural Language Processing (NLP), Fuzzy Logic, and advanced Machine Learning (ML) algorithms to make business processes more efficient, optimize cost, eliminate human error, and mitigate risk.

Karan Yaramada, CEO (Chief Executive Officer) of Kanverse.ai said, With the Iolite release, we are bringing new innovative features to our existing offerings. The new out-of-the-box integration with COINS ERP will open doors for new customers to experience the power of Kanverse. As a result, Kanverse AP invoice automation and the insurance document processing products are uniquely positioned to deliver unprecedented business benefits to all our customers.

Kanverse.ai Overview

Kanverse is a Hyperautomation cloud offering that can support various use cases across the enterprise to remove bottlenecks, streamline business processes, and minimize manual touchpoints across workflows. Kanverse provides a decision-making and analytics engine, conversational and programmatic interface and out of box connectors for interfacing with users and system of records where enterprise data is maintained. Learn more at: http://www.kanverse.ai

Originally posted here:

Kanverse Iolite Release Brings New Cutting-edge Features to Its Existing AP Invoice Automation and Insurance Document Processing Products - Business...

At the most basic, automation software is designed to turn repeatable, routine tasks into automated actions. It's used in Business Process Management (BPM) and Robotic Process Automation (RPA), among others.

The next step up is process automation. Process automation uses automation software to manage business processes. It streamlines rudimentary, repetitive tasks, and can turn several similar business processes into a single action with a few quick keystrokes.

Well known benefits of process automation include increased productivity and efficiency because automation leaves the menial jobs to computers, such as process mining. This frees the human workforce to produce more in ways that require human logic, thinking, creativity and decision making.

Integration automation is higher up in the evolution of automation software. Known as "digital workers", these software bots can be "trained" via recorded workflows. Once a process is built it requires very little human intervention. Digital Workers can become part of an integrated human/robotic workforce.

The final step of automation software is artificial intelligence (AI) automation. The added functionality of AI means the automation software can use past experience to improve how they perform the tasks required of them.

An example is AI-powered chatbots. Unlike basic chatbots, a software bot with AI ability is able to use natural language processing (NLP) to understand what a user is asking and give intelligent responses.

Throughout these four types of automation software, there are varying degrees. For example, you can have business process automation with a level of AI and machine learning. This allows the application to dig into your business processes and find other time-consuming tasks that could be better optimized.

Read more here:

What is Automation Software | Automation Anywhere

SOAR Platforms Help Automate Cybersecurity Tasks

Security orchestration, automation and response (SOAR) platforms are driving efforts to automate cybersecurity functions. These systems build on the information-gathering and correlation capabilities of security information and event management (SIEM) technologies by adding on automated response capabilities. When a SOAR platform detects that certain conditions are met, it can immediately trigger a playbook of activities designed to respond to those conditions.

READ MORE:Improve cybersecurity by moving from SIEM to SOAR.

For example, if an endpoint detection and response (EDR) system notifies a SOAR platform that malware was detected on an end-user device, the SOAR platform can automatically kick off a series of actions, including:

Modifying the network configuration to place that system on an isolated VLAN where it cannot communicate with any other devices, containing the damage caused by the infection

Triggering the EDR platform to remediate the malware infection, restoring the system to proper working order

Firing off a vulnerability scan that analyzes the systems configuration to confirm that it no longer poses a threat to itself or the network

Modifying the network configuration again at the completion of these tasks to restore the systems normal access

All those actions, which might previously have required hours of effort by cybersecurity professionals, can take place quickly when automated through a SOAR platform.

FIND OUT:This is what it takes to secure the cloud.

The workflows triggered by SOAR playbooks do not need to be strictly sequential in nature, either. The workflow above could be enhanced by adding conditional steps that occur based upon the results of prior steps. For example, Step 3 could be modified to take different actions depending on the results of the vulnerability scan. If the scan reveals that the system is remediated, the workflow could move on to Step 4 and automatically restore normal operations.

If, on the other hand, the scan reveals that the automated remediation was unsuccessful, the system could remain on the quarantined VLAN and the SOAR platform could open a ticket in the organizations IT service management platform to trigger a human investigation and response.

Once you have a SOAR platform in place, you can integrate it with many of your existing security tools to perform a variety of routine tasks. Its normally a good idea to start small and focus on efforts that have the highest potential payback in terms of time savings and pose the lowest risk to the organization. Lets take a look at three ways SOAR platforms can quickly add value to an organization.

Automate malware incident response efforts.Weve already discussed malware response as a prime example of the effectiveness of SOAR platforms. Given the burden that malware response places on security teams, automating these responses should be a high priority for any SOAR implementation effort.

Gather information for incident responders.Incident responders spend a lot of time gathering information as they attempt to triage and respond to cybersecurity events. SOAR platforms can automate much of this work by reaching into other systems and information sources to gather the basic facts before passing an event on to a human analyst for investigation. For example, if the SOAR suspects that a system is connecting to a botnet, the system can gather network traffic logs, threat intelligence data, user information and other records to prepare a dossier that analysts can use as they investigate the incident.

Process phishing messages.Every organization is deluged by phishing messages and most have a standardized workflow when users report these messages to administrators. Cybersecurity analysts might immediately remove the message from the inboxes of other users, add destination systems in links to a Domain Name System blackhole, identify systems that visited the link and run malware scans on them, block future messages from the same source, and perform other related actions. All of these tasks can be automated using SOAR technology.

LEARN MORE:Protect networks with next-generation endpoint security.

These three use cases are just starting points based on the types of automation that will benefit most organizations. As teams roll out SOAR technology, they should think about the pain points that they encounter and identify organization-specific use cases that will deliver the most value to their teams.

Original post:

Demystifying Security Automation for University IT Teams - EdTech Magazine: Focus on K-12

Automation technology has been on a path of steady growth for years. Having been one of the top industry trends in 2022 based on extensive data evidencing its increasing importance in the food sector, it is safe to assume that these newfound solutions are here to stay, and for a reason.

The future of manufacturing revolves around Industry 4.0, and AI is an intrinsic part of how product distribution practices are morphing to make room for machine learning and smart solutions. With this new era fast approaching, it is critical that manufacturers turn to automation and AI to deal with emerging trends within the food and beverage industry.

Related: How Food Manufacturers Will Tackle the Labor Crisis in 2022

The Covid-19 pandemic has accelerated the rise of new digital technologies, and as we emerge from the earlier, more challenging stages of the pandemic, we are faced with a world that relies even more extensively on automation.

During the pandemic, companies had to devise ways of coping with staff shortages and unstable work conditions, with safety regulations also affecting the amount of personnel that was able to be in a facility at any given time. In an era when relying on manual labor has become increasingly more difficult, food manufacturers find themselves in need of modern solutions, which automation technology and AI can offer.

Related: Food Firms to Expand Use of Automation in 2022

By investing in systems capable of carrying out tasks and processes consistently and efficiently, manufacturers can rely on processes that are significantly more risk-free while also complying with new, fast-changing regulations and addressing Covid-related concerns such as sanitation.

The Covid-19 pandemic has undoubtedly changed the way individuals think about hygiene, prompting them to consider how and where their food is produced and packaged. This wave of concern regarding food hygiene was fast-rising regardless of the lack of evidence that the virus could be transmitted through food, rendering new solutions capable of catering to these needs essential.

Automated procedures can significantly reduce the risk of food-safety hazards, putting consumers minds at ease. Ultimately, we should aim to shift our focus to whats going to benefit consumers long-term and therefore provide a return - as food hygiene concerns are unlikely to disappear any time soon.

Improving product quality should be the main point of focus for manufacturers, and a significant contributing factor to food safety and compliance is cleaning practices. Traditional cleaning procedures cannot compete with intelligent systems capable of detecting even the smallest of toxins or contaminants, drastically improving product quality as a result.

The procedure of cleaning equipment can also be optimized by employing AI, which can be programmed to detect even the smallest of substances that could potentially be harmful to food production lines.

While the increase in production of plant-based food is not a new trend, it is nonetheless on the rise, with demand having more than doubled in value since 2016. Producing plant-based foods requires different procedures to be implemented, particularly when they are produced in the same factory as meat products. By offering efficient and quick quality assurance procedures, automation can cut down on the time that is spent ensuring there is no cross-contamination.

And this is not the only issue at the forefront of consumers minds. Consumers commitment to sustainability remains strong despite the spike in popularity of packaged food throughout the Covid-19 pandemic, with environment-conscious shoppers now returning to their pre-pandemic habits.

In this context, raising concerns about food wastage has become relevant again, and AI may just hold the key to developing stable processes to contribute to the sustainability cause. As well as being programmed to reduce waste and therefore prevent edible food from being disposed of by accident, AI technology can also be employed to collect useful data and in turn, develop algorithms that can consistently prevent waste within a supply chain.

Automation technology can improve the efficiency of overall manufacturing projects in a variety of ways, and open a world of previously inaccessible solutions. As it is paving the way for new routes within the food and beverage industry and beyond, it is not surprising that artificial intelligence is deemed to be the future.

Automated software can provide traceability within the supply chain by collecting and storing data that can be accessed later on by manufacturers to find faults in a system or procedure or identify the source of issues or time delays. Additionally, AI can operate in environments that could be unfit for humans, such as extremely hot or cold environments, and even contribute to producing food of higher quality by identifying ideal growing conditions for fresh produce, resulting in better flavor, and thus better products.

Implementing automated procedures to keep up with demand and changing habits is increasingly more relevant in an era where improving food reliability is essential. And while changing our habits on such short notice Is not without its challenges, AI can be programmed to quickly change the way activities or tasks are performed, ultimately providing a great return on investment by allowing manufacturers to rapidly adapt.

Manufacturers and businesses must seek expert advice to help safely manage operations that incorporate automation technology and AI.

Ian Hart is the business development director at adi Project, a division of the engineering firmadiGroup. The group has experience providing tailored engineering solutions designed to efficiently address clients needs, no matter how complex or ambitious, while also preparing them for the future.

More here:

AI Holds the Key to Automation in the Food Industry - Design News

Managed services News C.J. Fairfield July 22, 2022, 02:08 PM EDT

Digitizing engineering and manufacturing is our clients next digital frontier, says Aaron Saint, North America lead for Industry X at Accenture. Accenture has deep digital expertise, Eclipse Automation is a leader in advanced automation capabilities, and combining these two capabilities will position Accenture better than ever to achieve this digital frontier.

Mammoth solutions provider Accenture will acquire Ontario, Canada-based Eclipse Automation to help clients build factories of the future by further enhancing robotics solutions and digital technologies.

Eclipse Automation specializes in manufacturing automation and robotics solutions for products in life sciences, industrial equipment, automotive, energy and consumer goods companies, such as electric vehicle batteries and wearable blood-glucose monitors. Their solutions include automation control systems and production machines and robots.

Financial terms of the deal were not disclosed.

Digitizing engineering and manufacturing is our clients next digital frontier, Aaron Saint, North America lead for Industry X at Accenture, told CRN. Accenture has deep digital expertise, Eclipse Automation is a leader in advanced automation capabilities, and combining these two capabilities will position Accenture better than ever to achieve this digital frontier.

[Related: THE 9 BIGGEST ACCENTURE ACQUISITIONS OF 2022 (SO FAR)]

He said Accenture has recently seen many companies bring production of goods back to local markets to combat supply chain shortages.

Accenture and Eclipse Automation together have the technology and training capabilities these companies need to develop a digital industrial workforce in markets where manufacturing skills are already scarce, he said.

Eclipse Automation was founded in 2001 and has offices in Canada, the U.S., Hungary, Germany, Switzerland and Malaysia. About 800 employees will come over in the acquisition.

For two decades, we have been leaders in delivering advanced automation solutions and high-tech manufacturing know-how to clients across multiple industries, said Steve Mai, CEO of Eclipse Automation, in a statement. By joining Accenture, we can also bring the advantages of data, AI and the cloud to our clients facilities at a scale that no other company can offer them.

The company will join Accenture Industry X, which will allow Accenture to offer automated production lines that leverage the cloud, data and artificial intelligence, making factories and plants more productive, sustainable and safe.

The acquisition is about scaling Accentures existing manufacturing automation and robotics capabilities, Saint said. Accenture started to build these capabilities with Pollux in Brazil, which engineers and deploys materials handling and autonomous mobile robots. Pollux has paved our way into autonomous robotics systems. In combination with all the capabilities Accenture has been building organically and through acquisitions, we will be able to offer a full turnkey end-to-end manufacturing solution for our clients at scale.

CJ Fairfield is an associate editor at CRN covering solution providers, MSPs and distributors. Prior to joining CRN, she worked at daily newspapers, including The Press of Atlantic City in New Jersey and The Frederick News-Post in Maryland. She can be reached at cfairfield@thechannelcompany.com.

Read more from the original source:

Accenture Buying Eclipse Automation To Reinvent Manufacturing With Robots - CRN

Hypen automated kitchen solutions.

Courtesy: Hyphen

Chipotle said Thursday it's investing in two companies that have the potential to accelerate its growth one that automates kitchen operations and another that makes plant-based versions of chicken and steak with mushrooms.

The Newport Beach, California-based company said Cultivate Next, its $50 million venture fund, will invest in Hyphen and Meati Foods.

Hyphen uses robotics to automate portioning out bowls and plates without the need for staff, Chipotle said in a release. Hyphen says its technology can make over 350 meals an hour.

The investment comes amid nationwide staffing shortages and is not Chipotle's first foray into automation investment. Last year, the company invested in Nuro, an automated delivery company, before creating its Cultivate Next fund. And his year, the company piloted Chippy, an autonomous machine that cooks and seasons Chipotle chips.

"Our goal is to drive efficiencies through collaborative robotics that will enable Chipotle's crew members to focus on other tasks in the restaurant," Chipotle's Chief Technology Officer Curt Garner said in a statement sent to CNBC .

Meati Foods, which received the other Cultivate Next investment, uses mushroom root to create plant-based chicken and steak alternatives. With the help of Chipotle's venture fund, Meati said it secured $150 million in its latest funding round.

Chipotle said in its release that plant-based options have been a priority for its menu in recent years. The company said it has not started the process of validating Meati products for inclusion into its menu.

Chipotle did not specify the dollar amount investments in Hyphen or Meati.

Read the rest here:

Chipotle announces investments in startups focusing on kitchen automation, plant-based alternatives - CNBC

With a modern, data-driven approach, companies can deliver enhanced user experiences by adding essential automated features that users cant live without.

Product and engineering teams are often faced with conquering a persistent end-user problem related to the hiring process at their organization unnecessary time spent on manual tasks such as interview scheduling and candidate communication. Applicant tracking systems (ATS) can be incredibly useful and allow product teams and engineers to help tackle this problem.

However, a common problem with ATS platforms is recruitings inefficiencies. This presents an opportunity for more connected and automated solutions. The simplest and most effective route to capitalize on this opportunity is through utilizing rich communications data that can unlock efficiency, productivity, and more engaging experiences. Companies can realize significant revenue gains by implementing rich productivity and digital experience features.

Free up Schedules with Automation Features

A primary goal for product and engineering teams is automating administrative tasks since the teams are often hampered by a backlog of features to build. Productivity features often cannot be implemented fast enough to keep up with increasing customer demand. Thus, product leaders are forced to make roadmap tradeoffs and release products that fall short of essential needs just to meet the deadline. While these products offer foundational capabilities, they lack the desired features to transform the recruiting experience by optimizing end-user efficiency and eliminating manual tasks.

Recruiters and HR teams must constantly juggle tasks, such as scheduling and conducting interviews, screening candidates, creating engaging job postings, vetting, and selecting the right candidate. So, they tend to gravitate toward features that automate and streamline the tedium of hiring new workers. This process can take a significant amount of time, usually several weeks or months, and often involves tracking and manual coordination. These mundane activities quickly add up, with the average recruiter spending 8 hours each week on administrative tasks that can be easily automated. Since this process is so cumbersome, 56% of recruitment firms have a dedicated interview scheduler on staff just for arranging in-person or video meetings.

See also: Hyperautomation is on the Two-Year Horizon

Why Companies Need to Unlock Productivity

Creating modern productivity and digital transformation features and experiences combines elements of cloud communications services, API platforms, low-code development tools, business process automation, and AI software development kits. ATS solutions that leverage these tools allow recruiters to increase their productivity by over 20%.

To help accelerate the product roadmap and simultaneously increase productivity for non-technical teams, product teams and developers need to solve these types of challenges at every stage of the software development lifecycle. Taking an out-of-the-box approach to building a modern ATS solution will help level up the companys recruiting needs. Benefits include:

See also: 5 Steps CIOs Can Take to Democratize Automation

How to Enhance ATS Platforms

Recruiters reported that the number one interview scheduling challenge is finding a time on calendars that works for all participants. Scheduling takes up so much time that 60% of recruiters report losing candidates before they can arrange an interview. Recruiters are not only wasting their time, but the hiring company is also missing opportunities to innovate and grow through its talent.

With a modern, data-driven approach, companies can deliver enhanced user experiences by adding essential automated features that users cant live without. Thus, recruiters and hiring managers can spend less time scheduling, following up, and sifting through emails. Instead, they can focus on improving the candidates experience and optimizing their interview processes. Its an easy adjustment for product teams who want a competitive edge and to differentiate themselves in a crowded market.

There are a plethora of benefits waiting for companies who emphasize and leverage rich datasets and productivity-driven features and solutions. A recruiters productivity increases by over 20% when ATS solutions leverage automation and data extraction proving to be an invaluable resource for teams. Teams that fast-track the addition of basic productivity and automation features can better focus on their strategic roadmap.

More:

Applied Automation: Increased Productivity for Applicant Tracking Systems - RTInsights

"Automation" has become a buzzword in cybersecurity circles. That is not surprising in an environment where security specialists are in short supply and under intense pressure to defend the business against a huge variety of threats from innumerable different sources. Using technology to do at least some of the work seems like a no-brainer. Nevertheless, it seems that organizations are finding it hard to get the right approach to cybersecurity automation.

Threat Quotient conducted research last year that found resources, time and a lack of trust in outcomes are preventing companies from realizing the benefits of automation. In a recent webinar, myself, Nabil Adouani, CEO of Strange Bee and co-founder of The Hive Project, and our Global VP of Threat Intelligence Engineering Chris Jacobs discussed the current state of automation, the expectations around what automation can actually achieve, and what this means for implementation in the real world.

From automation to orchestration and XDR -- all sides of the same coin?

One of the challenges around automation is defining what we mean by the term, and where it differs from orchestration. Really, automation is anything that replaces a manual human-driven activity with a computer-driven alternative. It has applications across the technology sector wherever there is a repetitive manual task that would be better done by a machine that never gets bored or makes mistakes.

In the incident response area of cybersecurity, automation can be used at any stage of the process. Examples include ingesting alert data, enrich alerts, and even automating elements of response. Often automation and orchestration seem to be used interchangeably, but there should be a distinction. Automation is the conversion/adaptation of a single manual process to be completed by machine, whereas orchestration is applied to a multi-stage workflow involving multiple different tools, which are automated and brought together to execute a process.

When it comes to XDR, there is further uncertainty around what this means. Analyst company Gartner suggests that XDR should have a minimum of three elements, such as endpoint detection and response, security incident and event management, and incident response capabilities on your platform. This would constitute XDR and orchestration could also be part of coordinating a series of automated actions based on the technology capabilities of the platform.

However, despite all the buzz around automation, orchestration, and XDR the path to implementation has not proved easy.

Orchestration is not a silver bullet

On the face of it, orchestration is a no-brainer, lifting the burden of repetitive tasks and saving time so cybersecurity teams can focus on higher-value activities. Yet adoption remains limited. Industry observers have even seen examples where businesses shifted from having no orchestration, straight to full orchestration, and then back to no orchestration again because they found they were spending all their time and resources fixing the automated workflows to function properly. They came to the conclusion that a simple script could work just as well for their use case.

Chris Jacobs advises that teams shouldnt assume that by buying and installing a platform theyll suddenly find themselves "magically" capable of doing things they werent doing before. First, they need to look at what processes they currently undertake manually and identify how these will benefit from orchestration into an automated workflow on the platform.

Nabil Adouani suggests that another reason for low adoption relates to the number of existing tools already in use. When there are already a lot of tools in play adding an orchestration platform that must be maintained actually increases the pressure on teams -- the exact opposite of the desired effect. If security professionals who want to be focusing on security need to frequently add new use cases, update workflows and work on integrations, this may lead to task avoidance and low adoption of the tool.

Deciding where to start

Organizations can feel overwhelmed when faced with the potential scale at which they could automate cybersecurity detection, management, and response, so where is the best place to start?

First, decide what types of incidents you want to handle with the tool. Then look at what you are already doing and where you are doing it when an incident occurs. So, for example, you might be using spreadsheets, one note, and emails to record and handle incidents, following a manual playbook. Look at that process and work out which elements could be automated, and then orchestrated into a multi-stage process in the platform. This approach has the added benefit of overcoming lack of trust in the outcomes of orchestrated processes. If you know what your process outcomes typically look like before you orchestrate them, you will find it easier to rationally accept a similar outcome from the orchestration tool.

Detection and vulnerability management are strong use cases for automation, and we recommend businesses put the majority of their focus here initially. Network detection, email security, and endpoint detection are all areas where, once issues are identified, multiple automated actions can be launched, such as informing the relevant stakeholders, enriching the alert data, and prioritizing the actions needed to mitigate the issue. In the case of vulnerability management, scanning identifies the weaknesses, and an automated workflow can share it with the people that need to action remediation.

It is also important to understand that the level of automation and orchestration that is appropriate will depend on the use case. Very few organizations will want to remove human oversight entirely from a process. For example, in patch management, its not advisable to automatically patch all your servers because the tool has identified a vulnerability and an available patch; there must be human input. Instead, you can use automation to find the right combination of compensating controls, so when the tool identifies a vulnerability, it automatically sends alerts to the relevant stakeholders so compensating controls can be put in place before the patch is implemented.

One of the major advantages of using a centralized platform is that all teams are using the same data and starting from the same point. This helps get cross-disciplinary IT and security teams working together and starts to break down the silos that often exist between departments.

In summary, when starting out with automation, first identify the repetitive, time-consuming workflows you already undertake that can be orchestrated. Then design the workflow with the appropriate balance of automation and human input for the use case, focusing initially on the detection phase before determining what aspects of response can or should be automated. Finally, explore how access to the tool can go further to break down silos between departments and get all teams working effectively together on a unified security mission.

This approach should reduce some of the pain points around implementing automation and ensure organizations are realistic in their expectations of what they can achieve.

Image credit: iqconcept/depositphotos.com

Yann Le Borgne is International VP of Threat Intelligence Engineering, Threat Quotient

Read the rest here:

Automation in cybersecurity: Overcoming barriers - BetaNews

UiPath is taking additional steps to strengthen its relationships with CIOs as leaders of automation projects, and to leverage the experiences of its CIO customers to expand usage of automation tech.

The company recently launched a CIO Automation Council made up of 15 customer tech leaders, and it continues to take steps to raise the profile of CIOs and help them drive better outcomes in their companies. The councils goals include expanding citizen development, improving employee experiences, and taking on more advanced use cases with automation technology.

I think CIOs are the most underrated professionals out there, says Rob Enslin, recently appointed co-CEO of Uipath. The demands on their organizations, and their roles, are evolving constantly. They need to integrate an ever-expanding range of systems, from ERP to procurement to expense reporting and much more. The job to keep them integrated is a complex role, and we should be the answer for integration for all CIOs in the automation economy.

Theres increasing evidence that CIOs are playing a bigger role in automation projects, says UiPath Chief Marketing Officer Bobby Patrick. The companys internal data shows an 11% year-over-year increase in the number of CIOs who are leading automation projects enterprise-wide, Patrick says. Theyre also embracing opportunities like the Automation Council: All 15 of those invited to participate accepted and joined the council.

We see CIOs taking it over, Patrick says. Were encouraging that. We know its important from a governance perspective, control, and security to have a well-run end-to-end program and CIOs are in a strong position to do that because they deliver services across diverse departments and functions.

Among the councils core goals is to foster citizen development of automation apps. Consider a low-code/no-code capability that lets automation software observe an employee in a retail store as well as learn and identify where bottlenecks are, generating code that can help to quickly solve problems with automation.

CIOs such as those on the automation council can help drive such outcomes by spreading the word and speaking to fellow CIOs as peers. We want to let them tell others in the language they can all understand, Patrick says. People dont want to hear that from vendors.

Another goal of the council is to help drive better employee experiences through automation: Think automating mundane, time-consuming tasks so people can do work that requires more advanced thought processes. One of the beauties of automation is that its very addictive, Patrick notes. Once an employee learns that something they hate doing can be done by a software robot, its not only addictive, its inspiring.

Employee satisfaction and engagement go up when robots are in place because they offload the mundane and boring in favor of higher-level functions. By actively helping with skills transitions, you can help upskill and reskill to help workers to not lose work but help transition to roles that are more valuable, Patrick says.

The CIO Automation Council members are:

For more exclusive cloud coverage, check out Cloud Wars Horizon here:

View original post here:

UiPath Taps CIOs To Drive Expanded Automation Usage - Acceleration Economy

The automation of lab work and data processing can reduce the impact of human error, improve data reliability and help optimize workflows and processes in the lab.

At the recent Future Labs Live conference, Technology Networks spoke to Mathew Keegan, head of applications engineering at Automata. Keegan discussed how automation in the lab was recently adopted to improve the safety of lab practices in a COVID-19 testing facility.

Keegan also highlights how automation is already enhancing the lab experience, the challenges it faces and where it may head in the future.

Molly Campbell (MC): Can you discuss the role that automation is already having in the laboratory, and how you envision that will change in the future?

Mathew Keegan (MK): The use of robotics and automation in labs is already improving the precision and speed of experiments and research, enabling scientists to spend more of their time thinking about new and innovative ideas. For example, automation empowers lab technicians to process and analyze higher volumes of data with greater accuracy and precision. It enables this by automatically inputting data into reports, reducing the number of errors in manual reporting and improving the reliability of data. From drug discovery to lab-grown meat, automation gives scientists the opportunity to explore new, more accurate ideas on a larger scale.

Going forward, were likely to see many more companies taking a capability-first, not capacity-first, approach to automation. With start-ups and scale-ups pumping out innovation at an ever-increasing rate, automation will have to adapt to high-growth situations where scientists are moving away from traditional, fixed systems. The increased capacity allows organizations to scale, helping to utilize lab space better and potentially bringing expansive commercial benefits.

MC: How can automation in the lab empower scientists to collaborate?

MK: Unfortunately, manual data collection is still the norm in many labs, and the risk of lost results and human error that this introduces can make it difficult for scientists to share accurate information with each other. Automated data collection allows scientists to spend more time engaging with their research and form new ideas using data they know is accurate. When paired with cloud solutions, scientists can work together from all over the world without having to endure the tedious task of manual data collection and entry.

MC: Can you discuss Automatas strategies for optimizing workflows and processes in the laboratory?

MK: When you link multiple automation technologies, you can automate entire workflows in the lab. Traditional workflow automation systems are often large, rigid structures that cannot be altered or changed giving labs little flexibility to innovate or change how they work. At Automata, were moving away from this traditional style to what we define as a capability automation approach.

Efficient automation requires processes to be agile and adapt to the changing needs of a working lab a series of capabilities, rather than a set of fixed steps. Opening up fixed systems and breaking them into modular products gives lab technicians the flexibility to add or remove equipment depending on their needs, empowering them to challenge the norm and discover new ways of working.

MC: What are the key challenges associated with introducing automation into a laboratory, and how does this vary across different labs?

MK: Often, the biggest challenge across labs is that scientists can be hesitant to embrace new technology like robotics and automation. Thats because they prefer to work with whats familiar to them or they dont often see large-scale automation projects to compare and see the benefits.

For example, while the diagnostics industry is one that can hugely benefit from the technology, it is held back by its hesitance to move towards newer methods. Over time, the industry has taken to sticking with the same off-the-shelf equipment such as liquid handlers, because they know how to use it and they trust it. However, this can be limiting for scientists in the long term and leaves little room for change and growth.

As the results of diagnostic processes have real impact on how patients are treated, a high level of accuracy is essential in the lab. Due to this, scientists want to be as close to the process as possible and can feel hesitant to trust the hands-off nature of many large-scale automation projects especially when coming at it alone. Partnering with an automation provider can help them make the jump into the unfamiliar and understand the long-term gains that can arise from automation.

MC: Are you able to discuss any case studies in which automation has significantly enhanced a scientists experience in the lab?

MK: We recently worked alongside the University Hospital Southampton NHS Foundation Trust (UHS) to automate their COVID-19 saliva testing program, which required the testing of up to 100,000 saliva samples a day. The UHS was tasked with delivering a testing program that covers the local population of Hampshire and the Isle of Wight and needed both an automation system capable of working at scale and one that was flexible able to pass off problematic saliva samples for manual processing. Working alongside engineers from the program, Automata designed and developed automated liquid handling systems that can be reprogrammed live on-site to meet changing requirements. The results have been transformative with the UHS now able to deliver hundreds of thousands of tests per day, reducing the chance of human error. It also made lab practices safer for staff, removing scientists from potential exposure to biohazardous substances and protecting them from infection.

MC: After attending the Future Labs Live event, what is your perspective on the lab of the future?

MK: Automation gives labs an opportunity to catapult into the future. A huge step forward is scientists realizing the true benefits that technology can offer and this change in mindset was certainly present at Future Labs Live. I left the event optimistic that very soon, were going to see more labs where people and robots are working side by side.

In the next five years, were going to see the emergence of labs that leverage automation to speed up sample preparation and establish high-throughput versions of complex workflows. All this while minimizing the risk of cross-contamination, eliminating human error and saving time and resources. We may even start to see lights out labs labs that operate 24 hours a day, maximizing their efficiency and shortening schedules for faster delivery of results. Making the lab of the future a reality means not only allowing scientists to achieve more in the lab, but helping organizations achieve their wider objectives such as bringing drugs to market faster.

Mathew Keegan was speaking to Molly Campbell, Senior Science Writer for Technology Networks.

Original post:

Automation in the Lab of the Future - Technology Networks