Category Archives: Artificial Intelligence

AI will certainly have an impact on the way that retail accounting work is done, but there is still debate as to the depth and timing of that impact

Artificial intelligence (AI) is all everyone in the business world seems to be talking about today, everything from how it will be used to improve business processes, and which kinds of employees it will replace. And many corporate chief financial officers (CFOs) already are evaluating the potential of AI as a way to increase profits while reducing costs.

Further, a new generation of chatbots is taking over online customer service for businesses, while many firms are using ChatGPT instead of freelance writers to develop content for blogs, websites, email campaigns, and social media posts. Others are using AI to analyze customers online activities to better boost the effectiveness of targeted email marketing campaigns.

AI is also beginning to make baby steps into corporate accounting departments. A new generation of accounts payable and payroll platforms uses rudimentary AI to read scanned invoices, bills, payroll records, 1099 and W-2 forms, and tax notices and then automatically categorize and enter this information into the departments accounting software.

While these uses of AI can help free up time for accountants and bookkeepers who once had to enter this information manually, there is one critical area of accounting where AI is unlikely to make headway soon account reconciliation for retailers and restaurants that generate significant revenue through online sales.

And thats unfortunate, because in this era of razor-thin margins CFOs need to have access to accurate profit & loss information every day. The accountants and bookkeepers they rely on to deliver this information, however, are getting so frustrated by what has become a very labor-intensive and time-consuming process that many are quitting in droves and CFOs are having a very difficult time replacing them.

In an ideal world, an AI-based account-reconciliation platform would automatically download all sales and payment data from every system used by every location, analyze and categorize adjustments, flag exceptions, and prepare summaries for the accountant to review and approve before entering this information into the companys accounting system.

Unfortunately, this isnt going to happen anytime soon. And heres why.

Not only is gaining access to sales data difficult, but an even harder part is making sense of the data. The ability of an AI system to learn is completely dependent on the quality and consistency of the information that is fed into it. AI works best when its trained on structured data that follow predefined rules.

This isnt an issue for payroll records, tax forms, bills, and invoices, which tend to use relatively consistent data structures that make it fairly easy for AI systems to learn and process. Unfortunately, no such consistency exists in the ecommerce world. Each vendor uses siloed sales data formats, with widely variable and often-opaque structures for reporting adjustments. Indeed, some even use their own custom-built platforms with no proper reporting for accountants.

Take state sales taxes, for example. Platforms like Shopify automatically pay taxes on sales made through Instagram and Facebook Marketplace, bt Shopify doesnt clearly label tax adjustments in its transaction records. Instead, its up to the retailers accountant to identify sales taxes and countless other non-annotated adjustments in transaction records, make sure that net sales and deposits match, and resolve exceptions when they dont.

Every time a retailer signs up for a new ecommerce platform or service provider, this creates yet another sales data decoding challenge for accountants and bookkeepers who are already struggling to master existing platforms.

Unfortunately, CFOs cant afford to ignore these problems, because burnout among bookkeepers is becoming a key challenge for retailers.

Further, this is a relatively new phenomenon. Before sales apps like Stripe andShopKeeplaunched in the early 2000s, retail account reconciliation was relatively easy. Most brick-and-mortar retailers generated all of their sales on-site and most accountants and bookkeepers only had to reconcile cash and credit card transactions and download sales reports from a single point-of-sale system.

In recent years, however, everything has changed. Retailers are using upwards of five sales and payment platforms without scrutinizing the quality of the sales reports generated by the systems.As a result of these decisions, many retailers are paying the price in terms of increased attrition among their accountants and bookkeepers.

How bad is the problem? Between 2000 and 2022, more than300,000 accountantsquit their jobs, and today the average turnover rate among corporate accountants is 13.4%.And the outlook for bookkeepers isnt much better. Job growth is expected to decline by 5%through 2030.More problematic is that experienced and knowledgeable veterans are leaving the industry in increasing numbers. As a result, today the average bookkeeper has less thantwo years of experience.

Unfortunately, a universal ChatGPT-style AI solution for retail accounting isnt on the immediate horizon. Not as long as the tax & accounting industry doesnt come together to develop standardized data structure conventions.

However, progress is proceeding on a decentralized scale. Accounting software developers are beginning to move accountants towards data workflows that can convert siloed data-reporting formats into digestible sales data that can eventually train AI systems to process them automatically.

And some of these developers already offer solutions that can automate account reconciliation for retailers using many online sales platforms. For example, automated accounting firms like Bench and Pilot can automatically collect, analyze, and reconcile sales data from systems like Square and Shopify for their accounting clients.

In the meantime, CFOs who arent quite ready to partner with outside accounting automation firms can still support their accountants and bookkeepers by giving them a voice when it comes to choosing or changing sales platforms.

Vendors should be willing to provide samples of downloaded sales reports and transaction records they can review by accountants to assess how much effort it could take to decipher them. And accounting professionals should have the opportunity to meet with members of the vendors development team to ask questions and express concerns about any AI-driven software solution.

CFOs also should be willing to reject any vendorwhose sales feeds would create additional and unnecessary work fortheir accountants and bookkeepers. Or, at the very least, press vendors to explain how they are improving the companys financial reporting and whether the sales data can easily be processed by accounting automation platforms, in case the retailer chooses to partner with one of these firms down the line.

Keep in mind, the easy part is adding new ecommerce platforms to your business. The more challenging aspect is finding and retaining tax & accounting professionals who are willing to work with sub-optimal systems. This is one situation where the value of human capital is far more important than simply making more sales.

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Artificial intelligence isn't transforming retail accounting, yet - Thomson Reuters

Exploring the Impact of Artificial Intelligence on Forensic and Genealogical Investigations

Artificial Intelligence (AI) is revolutionizing various sectors, and the fields of forensic and genealogical investigations are no exception. The integration of AI into these areas is not only enhancing the accuracy of investigations but also significantly reducing the time taken to reach conclusions.

In the realm of forensics, AI is playing a pivotal role in transforming traditional investigative methods. Forensic investigations often involve the analysis of vast amounts of data, which can be time-consuming and prone to human error. However, with the advent of AI, investigators can now process and analyze this data more efficiently and accurately. For instance, AI algorithms can sift through thousands of documents, images, and videos in a fraction of the time it would take a human investigator, identifying patterns and connections that might otherwise go unnoticed.

Moreover, AI is also proving instrumental in enhancing the accuracy of forensic evidence. In the past, the interpretation of forensic evidence, such as fingerprints or DNA, was largely dependent on the expertise of the investigator. However, AI can now analyze this evidence with a level of precision that far surpasses human capabilities. This not only increases the reliability of the evidence but also reduces the likelihood of wrongful convictions.

In the field of genealogical investigations, AI is similarly making a significant impact. Genealogical research involves tracing family histories and lineages, a task that traditionally required painstaking manual research. However, AI is now being used to automate this process, making it faster and more efficient. AI algorithms can analyze vast databases of historical records, identifying connections and patterns that can help trace a persons ancestry.

Furthermore, AI is also helping to overcome some of the challenges associated with genealogical research. For instance, historical records are often incomplete or inaccurate, making it difficult to trace a persons lineage accurately. However, AI can use predictive modeling to fill in these gaps, providing a more complete picture of a persons ancestry.

In addition, AI is also being used to analyze genetic data in genealogical investigations. This involves using AI algorithms to identify patterns in a persons DNA that can provide clues about their ancestry. This not only enhances the accuracy of genealogical research but also opens up new possibilities for understanding human evolution and migration patterns.

In conclusion, the integration of AI into forensic and genealogical investigations is proving to be a game-changer. By automating data analysis and enhancing the accuracy of evidence and research, AI is not only making these investigations more efficient but also more reliable. As AI continues to evolve, we can expect it to play an even more significant role in these fields, opening up new possibilities for understanding our past and ensuring justice in the present.

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The Role of Artificial Intelligence in Enhancing Forensic and ... - Fagen wasanni

INDIANAPOLIS (WISH) Humans have probably heard the phrase dogs are a mans best friend.

Now, it could be AI is a mans best friend.

Artificial intelligence has been a major topic of conversation as it continues to advance and become integrated with everyday life.

For people who grew up in the 1990s, the concept may not be a wild one. After all, we did have Tamagotchi handheld digital pets.

The more recent AI pets are a little more advanced than the electronic pocket pets.

Boston Dynamics and other companies have gone viral several times on social media with videos of their lifelike robot animals. Many of them can run, jump and even follow basic human commands.

China-based company Unittree boasts a robotic companion named the Go1. It walks on all fours as a dog or cat would, and has a following feature so you never have to worry about the robot running off.

According to the company website, there are other options, as well, like the Go2, which comes with a self-charging base for your AI pet.

Dr. Harvey Castro is a Dallas, Texas-based medical professional, and is an expert in AI in health care.

Castro says there are pros and cons to the possibility of artificial intelligence pets.

While robotic pets offer continuous companionship, low maintenance, elimination of allergy exposure, and even mental health support, AI companionship can also be limiting, Castro said in a statement.

Castro added, AI pets cannot replicate the complex and rich experience of caring for a real animal.

He also says they may not be the best for people when it comes to being active. Unlike real pets, A.I. pets dont encourage owners to engage inphysical activity, like walking or playing, Castro said in the statement.

Castro also mentioned the potential risks related to data privacy and dependency on AI pets for companionship, which could lead to the neglect of real-life relationships.

The long-term psychological and emotional effects of having AI pets, especially on children, are yet to be fully understood, Castro said in the statement.

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Is artificial intelligence the future of pets? - WISH TV Indianapolis, IN

Tuberculosis (TB) is a disease that spreads through the air when people cough, sneeze, or spit, meaning a person only needs to inhale a few germs to become infected.

Its a disease that has plagued human history and continues to kill people in swaths.

The World Health Organization (WHO) calculates that 10 million people across the globe fall ill with TB every year. And, although it is a highly preventable and curable disease, 1.5 million people still die each year because of it making TB the worlds top infectious killer, only falling short of COVID-19.

John Green, an author and philanthropist who often talks about TB on TikTok, puts it into perspective:

If you add up all the people who, in 2022, passed away due to conflict, homicide, malaria, typhoid, and cholera combined, it is still fewer than the number of people who died of Tuberculosis in 2022. What makes that fact crazy, of course, is that Tuberculosis is curable, he said in a video. Tuberculosis is caused by injustice; it is caused by inequitable access to healthcare.

But the WHO aims to end the TB epidemic by 2030 and researchers around the world are using the highest levels of technology to do so.

Take Vietnam, for example, one of 30 countries with the highest burden of TB globally. (An estimated 169,000 people became sick with TB in Vietnam in 2021).

FHI 360, a global organization that mobilizes research and resources to help people have access to healthy lives, and the National TB Control Program of Vietnam are starting at the helm: Accurately diagnosing TB so it can be treated expeditiously.

This effort, which employs the use of artificial intelligence to create a double detection system, works to diagnose and treat TB all while ensuring that patients receive high-quality care without suffering catastrophic costs.

You cant diagnose TB through a self-test, like you can with HIV, Anh Innes, MD, FHI 360s senior technical advisor for Tuberculosis says. You have to have an X-ray. So, to eliminate the disease, we must find the people with TB. Were trying to simplify the diagnosis to make it more point-of-care within the community.

This streamlined diagnosis uses an innovative approach called the Double X Strategy.

FHI 360, along with the U.S. Agency for International Development (USAID) Support to End Tuberculosis project, utilizes the Double X Strategy to combine AI data and direct human professional support to rapidly and accurately detect TB.

The approach uses both X-ray machines and rapid diagnostic machines, called GeneXpert reaching people both in hospitals and in community events with mobile units. Its a win-win-win-win, if we did our calculations correctly.

To detect the disease (or lack thereof), a person at risk of having TB receives a chest X-ray. If the X-ray is abnormal, that person then receives a sputum test with GeneXpert, which can identify M. Tuberculosis DNA.

The test is completed in two hours and results are returned in one to two days. If the test results indicate that the patient has TB, they are started on treatment right away.

In 2020, these partner organizations held 18 community health events in seven Vietnamese provinces, reaching people who live with a TB patient, as well as those with higher TB risks. This led to 52,868 chest X-rays.

Of those scans, 7,968 were determined to be abnormal for TB, and 7,747 people were then tested with GeneXpert, leading to 723 bacteriologically confirmed TB patients.

But where does AI come into play? As experts reach more people through high-volume mobile health screening events, X-ray analyses are aided by AI. Radiologists are able to interpret chest X-rays and quickly compare it with the findings developed by AI software for more accurate results.

In a recent study led by Dr. Frauke Rudolf from Aarhus University, researchers determined that the AI technology was able to match or even outperform professional radiologists in detecting TB.

In an analysis of the X-rays of 498 patients, including 57 diagnosed with TB, the AI software correctly identified 75% of the positive cases and showed an 85.7% accuracy rate in detecting negative results for patients who did not have TB.

The experiment was conducted on mobile phone photographs of chest X-rays, meaning this tech can be applied in underserved areas, where doctors can get a second opinion remotely by sending the scans to the AI.

FHI 360 and USAID use this technology in the Double X Strategy to maximize detection and subsequent treatment.

Using AI with chest X-rays helps ensure that people with TB are identified at all facilities, including lower levels of the health system where staff may have less experience interpreting chest X-rays, an FHI 360 blog post reads.

At community mobile health screening events, where one or two technicians may read hundreds of chest X-rays per day, AI helps avoid decision fatigue and over- or under-selection.

Since 2022, the project has utilized AI to read more than 100,000 X-rays.

These innovations are finding more people in need of TB care and preventative treatment, as well as finding more people who may not necessarily have classic TB symptoms. They have early-stage, subclinical TB, which is an area of emerging research, an FHI 360 press release states. In the past, many early-stage cases would not have been detected without current technology.

The Double X strategy has become Vietnams national TB screening strategy, allowing experts to meet people where they are and create the blueprint to a more holistic approach to battling the worlds deadliest infectious disease.

Developing comprehensive, flexible TB strategies that address all stages of the disease is the way to end TB, the FHI 360 blog post concludes. We must continue updating practices and leveraging new technologies to detect, cure, and prevent this ancient disease that continues to affect communities today.

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Artificial Intelligence Takes on the World's Deadliest Infectious Disease - Good Good Good

New Jersey, August 8, 2023 Artificial intelligence and related technologies seem to have promise as groundbreaking and transformative elements in many areas of modern life, including local government. But significant questions remain about these technologies, both on a fundamental level and as they relate to civic life.

These questions and more will be explored during a webinar titled The Impact of Artificial Intelligence and Related Technologies in Local Government on Thursday, August 17 at 12:30 p.m. ET. This free webinar is part of the Corporation for New Jersey Local Medias Community Engagement Series, which promote civic engagement by bringing together experts and journalists to discuss news of local interest and how it impacts our communities. Attendees can register to attend the webinar at: https://us06web.zoom.us/webinar/register/WN_H1grcEuASwegmJ-yVF3zmg.

Webinar panelists include: Senator Andrew Zwicker (D-Hunterdon, Mercer, Middlesex and Somerset), scientist and educator at Princeton Universitys Plasma Physics Laboratory; Professor Marc Pfeiffer, Senior Policy Fellow, Bloustein School of Planning and Public Policy at Rutgers University; Alex Parker-Magyar, editor, Madison Eagle, Florham Park Eagle, and Chatham Courier.

The panel will be moderated by Amanda Richardson, executive director of the Corporation for New Jersey Local Media.

We are pleased to host a webinar focused on an issue that is so timely and of such great importance to our communities, said Richardson. Our webinar series aims to bring light to issues of local and statewide importance by speaking with the people on the ground: reporters, analysts, activists, and politicians.

Generative AI is the newest technology that provides economic benefits for innovators but lacks societal guardrails for users, said Professor Marc Pfeiffer, who also serves on the Governing Board of the Corporation for New Jersey Local Media. We need to learn from the past and then walk (develop safeguards) and chew gum (deploy systems carefully) at the same time.

### Corporation for New Jersey Local Media builds strong communities through journalism and civic engagement. The organization seeks to enhance civic engagement by promoting professional community journalism, fostering public discussion of critical issues, and expanding access to educational programs. Learn more at http://www.newsweneed.org.

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Panel of Experts to Discuss the Impact of Artificial Intelligence on ... - InsiderNJ

By analyzing the movements of individuals wearing virtual reality (VR) headsets, researchers have demonstrated that a machine learning model can accurately predict personal data such as height, weight, age, marital status, and more. This highlights the potential privacy implications of artificial intelligence (AI) in VR, as personal data can be guessed without users explicitly disclosing it.

In a study conducted at the University of California, Berkeley, researchers were able to identify a specific individual among over 50,000 other VR users with over 94% accuracy after analyzing just 200 seconds of motion data. In another study, researchers accurately determined a persons height, weight, foot size, and country with more than 80% accuracy using data from 1,000 players of the VR game Beat Saber. Additionally, personal information like marital status, employment status, and ethnicity could be identified with more than 70% accuracy.

To analyze the data, the researchers employed a machine learning model that processed uploaded data from VR headsets, such as eye and hand movements. The model could easily identify factors like age, gender, ethnicity, and country. More nuanced information, including income level, disability status, health status, and even political preference, could also be inferred.

VR headsets capture data that traditional websites or apps cannot, such as gaze, body language, body proportions, and facial expressions. This combination of data intensifies privacy concerns and raises additional issues beyond those faced by conventional platforms.

Meta Platforms Inc., a major VR headset manufacturer, uses machine learning to fill in gaps in its knowledge of users, particularly since Apple limited the amount of data that can be tracked on its iPhones. VR headsets, therefore, represent an opportunity for Meta to collect more data to improve ad targeting and revenue generation through advertising.

Protecting privacy in VR headsets is challenging due to the necessity of collecting data like eye and hand movements. Encryption and limiting stored data are potential solutions, but companies producing VR headsets have incentives to collect information for marketing purposes.

Privacy controls and consumer awareness are currently inadequate in the VR space. The capabilities of AI, coupled with limited understanding of the technology among users and regulators, pose significant challenges for individuals to protect their privacy effectively.

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Blending Virtual Reality and Artificial Intelligence Raises Privacy ... - Fagen wasanni

Artificial intelligence (AI) has been recognized as the most disruptive technology since Q3 2021, and this holds true across various industries, including the retail sector.

Retailers are increasingly investing in AI with the goal of boosting sales, stabilizing supply chains, improving planning processes, and enhancing customer relations.

One area where AI is making a significant impact is in supply chain forecasting. Through machine learning, retailers can accurately predict demand by considering hundreds of influencing factors. This enables better planning across merchandising, supply chains, and operations, providing visibility into future demand for every product in every store and channel.

Retailers such as One Stop have already implemented AI forecasting solutions and have reported positive results. After just four months of using an AI forecasting solution, One Stop saw a 5% increase in store availability across their entire range, leading to a significant increase in sales.

AI is also helping retailers cut operational costs through the use of chatbots. Automated cashier-free stores, like Amazon Go, have been successful in reducing queues and operational expenses. AI-powered chatbots are being adopted by brands like Burberry to enhance customer service, improve searchability, and provide personalized product suggestions.

Pricing and clearance optimization software is another area where AI is transforming the retail sector. These solutions automate markdowns and clearance processes, eliminating manual tasks and reducing the risk of excess stock. Retailers can identify products for clearance and set optimized discounts based on desired outcomes. This helps improve margins and inventory turnover.

The use of AI in the retail sector is diverse and constantly evolving. Companies that embrace AI technology will position themselves as industry leaders, while those who overlook its potential may struggle to keep up with the competition. The adoption of AI will play a crucial role in determining the winners and losers in the retail sector of tomorrow.

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The Impact of Artificial Intelligence in the Retail Sector - Fagen wasanni

Overcoming IT Hurdles: A Comprehensive Guide to Solving IT Challenges with Artificial Intelligence

The world of information technology (IT) is constantly evolving, bringing forth new challenges that need innovative solutions. One such solution that has gained significant traction in recent years is Artificial Intelligence (AI). By leveraging AI, businesses can overcome a myriad of IT hurdles, from data management to cybersecurity threats, and improve their overall operational efficiency.

The first major challenge that AI can help address is data management. In the digital age, businesses generate and collect vast amounts of data. Managing this data, ensuring its accuracy, and extracting meaningful insights from it can be a daunting task. However, AI, with its machine learning capabilities, can automate data management processes, analyze complex data sets, and provide actionable insights. This not only saves time and resources but also helps businesses make data-driven decisions.

Next, AI can significantly enhance cybersecurity measures. With cyber threats becoming increasingly sophisticated, traditional security measures are often insufficient. AI can help by constantly learning from these threats and adapting security measures accordingly. For instance, AI can identify patterns in cyber-attacks, predict potential threats, and implement preventive measures, thereby providing a robust defense against cyber threats.

Moreover, AI can streamline IT operations by automating routine tasks. IT departments often spend a significant amount of time on mundane tasks such as system maintenance and troubleshooting. AI can automate these tasks, freeing up IT professionals to focus on more strategic initiatives. Additionally, AI can predict IT system failures and take corrective action before the issue escalates, thereby minimizing downtime and improving system reliability.

Another area where AI can make a significant impact is customer service. With AI-powered chatbots, businesses can provide 24/7 customer support, resolve queries promptly, and improve customer satisfaction. These chatbots can learn from past interactions, thereby enhancing their ability to resolve customer queries over time.

Furthermore, AI can help in resource allocation. By analyzing past data, AI can predict future resource requirements and help businesses plan accordingly. This can result in cost savings and improved efficiency. For instance, AI can predict when a business might experience a surge in website traffic and allocate resources accordingly to prevent website downtime.

Finally, AI can aid in decision-making. By analyzing data and providing insights, AI can help businesses make informed decisions. Whether its deciding on the best marketing strategy or identifying potential areas of investment, AI can provide valuable input that can drive business growth.

In conclusion, AI presents a comprehensive solution to various IT challenges. By automating routine tasks, enhancing cybersecurity, improving customer service, aiding in resource allocation, and facilitating decision-making, AI can significantly improve business operations. However, its important to note that the successful implementation of AI requires a strategic approach. Businesses need to clearly define their objectives, invest in the right AI tools, and train their staff to effectively use these tools. With the right approach, businesses can harness the power of AI to overcome IT hurdles and drive growth.

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Solving IT Challenges with Artificial Intelligence: A Comprehensive ... - Fagen wasanni

Twenty years ago, the advent of the internet led many to worry about their job security. Yet the rapid digitisation that ensued created millions of careers that didnt exist before. By 2018, digital jobs accounted for 7.7% of the UK economy.

History does tend to repeat itself, and right now, there are scores of headlines popping up every day about the latest threat borne of Silicon Valley; artificial intelligence (AI) and machine learning (ML). Thanks, in part, to a new wave of freely available AI-powered chatbots, businesses and consumers alike are becoming aware of the technologys extensive capabilities.

While this has opened up fierce discussion about regulation even among the brightest minds in tech, there is also optimism about how AI could revolutionise the enterprise. Rather than fearing it may replace everyones jobs there are many examples of why this wont happen in both technical and creative roles it is easy to see how it could make work more enjoyable by automating dull, repetitive tasks.

This is particularly true in growing businesses, where higher-level employees may be bogged down by mundane tasks instead of focusing on strategy and other complex responsibilities.

For instance, no one wants to dig around their desk or car footwells for crumpled-up receipts when submitting expenses. Similarly, most CFOs dont want to be stomping about workstations, chasing staff for paperwork. Dedicated expense management apps enable employees to take a photo of their receipt as soon as they get it, automatically drawing out the relevant data to start a pain-free submission process.

An example of this can be found with Barnsley Metropolitan Borough Council, which recently automated its expense management processes with Concur Expense, a solution from SAP Concur. The council wanted to eliminate manual processes and create digital workflows [to] provide the highest possible levels of service to residents. After installing Concur Expense, mobile teams (like social workers) could input expenses on the go through an app. The time saved in expense entry and the reduced number of human errors thanks to AI-powered automation decreased the average reimbursement time from six weeks to three days.

Implementing a T&E management software powered by AI has also helped Barnsley Metropolitan Borough Council focus on its sustainability. The data allows it to better monitor its grey fleet the personal vehicles being used for business purposes and therefore its carbon footprint too. The council can now make more informed decisions about its travel policy, and appropriately encourage employees to make use of public transport.

David Robinson, Service Director at the council, said: We want to adopt modern ways of working to give people the right work-life balance and attract the best talent. Concur Expense is a great example of how we can increase support for digital initiatives among employees by making sure theyre not out of pocket while we process claims.

Integrating AI into workplace software is nothing new, of course. But travel and expense management has been under-explored, despite being a data-rich area and, therefore, perfect for machine learning. There is also demand; research from Forrester Consulting has shown that 59% of decision-makers say that employee frustration with their expense process had a large or very large negative impact on the entire company.

Advanced algorithms can analyse and categorise expense data by recognising patterns and using natural language processing techniques. They auto-approve low-risk claims, eliminating the need for manual entry and reducing errors. As these algorithms process more expenses, they get better at knowing what is safe to approve without human intervention.

Automation reduces the chances of anything slipping through the cracks. Research has shown that 62% of finance leaders find that digital tools help them manage expenses more effectively across their organisations. Studies have also shown that over half of companies implementing an integrated travel and expense solution increase their scalability and flexibility.

Moreover, AI can defend the company against fraud by comparing the expense data against predefined rules and benchmarks and flagging any potential violations. It also helps organisations follow all compliance and regulatory requirements, something thats often only an afterthought. From a business intelligence perspective, too, technology can highlight cost-saving opportunities, generating reports for decision-makers from collated travel and expense data.

The minds at SAP Concur know that implementing AI and ML into finance processes can be intimidating. However, its software is well tried and tested, having been adopted by over 48,000 businesses since the early 1990s.

Expense management has been undergoing optimisation with AI and ML since long before other areas of corporate finance. Indeed, automating small, repetitive tasks like using Concur Expense to submit and approve receipts is a good starting point.

In the future, we can expect AI to completely transform expense management, resulting in increased company efficiency, savings from better financial management and minimised environmental impact. Its widespread implementation is expected to result in a 7% increase in GDP over the next ten years.

If you want to learn more about automating your expenses with SAP Concur, visit this website.

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The role of artificial intelligence in the world of the CFO starts with ... - TechHQ

As more businesses adopt artificial intelligence (AI) tools, venture capitalists (VCs) are putting more money into the industry.

Nearly three-quarters of global VCs invested in AI over the past year, with investors identifying AI as the technology with the most disruption potential, according to a recent survey by PitchBook and Collision.

Seventy-four percent of those surveyed said they made at least one investment in AI or machine learning (ML) startups in the last 18 months, and 14% claimed they had made more than six investments in the space.

The number of companies that use AI has also more than doubled since 2017, according to research by McKinsey. Service operations optimization, the creation of new AI-based tools, and customer service analytics are the most widely used cases of AI.

However, funding activities have taken a major blow due to uncertain macroeconomic conditions and rising rates. VCs formed $13 billion in funds during the first quarter of 2023, compared to $78.1 billion in the same period a year ago, according to EY. More than half of investors PitchBook surveyed said they arent looking to raise funds, while 54% suggested they believe that raising funds will be difficult in the next 12 months.

Despite being battered by economic headwinds and rising rates, nearly 68% of respondents claim that their pace of investment over the last 18 months remains near normal. Only 3.4% of respondents said that they have halted investments for the time being.

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Majority of Venture Capitalists Invested in Artificial Intelligence ... - Investopedia