Category: Artificial intelligence

Impact Of Artificial Intelligence On Accounting And Finance Industries

ABSTRACT

Artificial intelligence has been in place since the year 1956, but considering the recent momentous acceleration in the accounting and finance industry it has become the vital topic in business. It plays a foremost role in the way the functions are performed in an organisation. Recently, Artificial Intelligence has revolutionised the efficiency, quality and time taken to accomplish these functions in contrary to manual performance. In fact, the very same difference has sparked controversial debates.

There is no doubt the structure, working mechanics, required skill level etc. is altogether transforming with the operation of Artificial Intelligence to remain profitable in the economy and competitive in the market. In support to the well-known theory, the survival of the fittest, now professionals and employees are also expected not only to work in par with technology but also to control them. This, largely affects the attitude of individuals working in an organisation. Also, it is a discerning move from the management to manage the cost, learning curve and all other uncertainties.

Therefore, this paper mainly focuses on the aspiration of understanding the use of Artificial Intelligence in Accounting and Finance industries which in turn assess its effectiveness and performance. Since, employment is another major factor affecting our economy it is also essential to comprehend their value and their knowledge regarding the recent developments. Thus, this paper would be imperative to analyse the attitude and expectation of the professionals and also, the efficiency and evolution of these industries with the employment of Artificial Intelligence.

INTRODUCTION

Artificial Intelligence (AI) implies to the simulation of human intelligence that are programmed to think like humans and impersonate their activities. It presents opportunities to complement and supplement human intelligence and enrich the way people live and work.

India being one of the fastest growing economy and having second largest population in the globe has a substantial stake in the revolution of AI. It is not distinctive when it comes to the significance of AI in Accounting and Finance Industry. AI is more than merely robots that comes into one’s mind when trying to picture the word. It has been transforming these industries through various applications available, such as, data collection, chatbots, personal assistance, consumer interaction, risk assessment, cybersecurity, etc. without emotional and psychological factors affecting them. All the applications can be classified under the different categories of Artificial Intelligence – weak or strong or general centred on its capabilities and reactive machines, limited memory, theory of mind, self-awareness based on its functionality. Whatever maybe the application or the category of AI used by the industries, the aim of AI includes, 1. Learning, 2. Reasoning, 3. Problem solving, 4. Perception and 5. Language.

With technological advancements, AI has been evolving to beat its own previously set benchmarks and benefits. Since, the world seems to be transforming with AI, it is no doubt that it has created a fear of employment and replacement among the people as. In contradiction, it is also said that AI is only to eliminate tedious mundane jobs enabling professionals to perform more higher-level tasks, lucrative analysis and counselling. Also, it is believed that new jobs will be created through micro-economic and macro-economic effects. As of October 2019, a joint research conducted by the National Business Research Institute and Narrative Science stated that only about 32% of monetary service providers have adapted or embraced AI. In addition, a joint survey conducted by EY and Invesco stated that the adaptation of AI is expected to be 64% in the ensuing two years. Thus, AI has become the inevitable by gaining constant attention from everyone including the Government of India. The Indian Government conducted and published a discussion paper on National Strategy for AI with the help of NITI Aayog. Therefore, it is imperative to recognize the level or degree of impact AI has on these industries and the work force to analyse the current work environment and the future.

CONCEPT OF ARTIFICIAL INTELLIGENCE USED

Almost all the industries are now aware of the existence of AI and the possible benefits they could gain from its application if due care and diligence is taken. The following are some ways in which this fast-moving technology has been put to use for everyday activities by the accounting and finance industry. To begin with, AI based invoice management systems helps in payment/receiving process by saving time, cost and errors. Secondly, AI can examine a supplier’s tax details and credit scores all by themselves without a need for human hand and provide the suppliers with required data by setting up query portals. Thirdly, with the use of application programming interface, records maintained in different systems can be processed together which helps avoid massive amount of paperwork. Fourthly, with digitalization financial transactions can be both recorded and audited. It has highly improved the efficiency and productivity of an organization by helping them meet their goals and make better judgements. It also helps in acquiring and securely consolidating financial statement. If any breach or fraud has been committed then the AI is powered to alert the management. Fifthly, the most recent development is the introduction of chatbots. It has been made user friendly that consumers find their queries solved within minutes rather than waiting in line for customer care services.

AI also helps companies in making smart credit and underwriting decisions which helps them reduce predicted risks and losses. It also helps them review a client and provide loans more securely and avoid the issues of non-payment. Machine learning, a subset of AI is also used to create models which helps in forecasting and prediction of data. AI is also used in identifying large data sets and analysing patterns that can be used to make strategic trades. It has been used by financial institutions and especially brokers. Most important of all, AI is a major key to improve cybersecurity and fraud detection since everything is now stirring online. Thus, AI has become a necessity.

IMPACT OF ARTIFICIAL INTELLIGENCE

With the rise of neo banking and never-ending expectations of consumers spread around distinct geographical locations accounting and finance industries started gracing AI at the staff level which has steadily climbed the ladder and tends to continuously do so. It has greatly transformed and impacted the industries in the following manner;

Positive Impact of AI

• It has enabled hyper-personalisation which helps them provide customised services suitable to every individual needs. AI has shaped these industries by enabling self-service which provides customised solutions to them anywhere and anytime. This led to the rise of online banking and e-trading etc. Also, the organisations method of consumer interaction has vastly changed. No longer are there queues to get basic questions answered or phone calls on hold. Chatbots and online query services which are accessible 24/7 has changed the game.
• It has created a provision wherein the back-office operations can be fully automated which reduces the human requirement in those areas. In fact, it has been augmenting the human work. The industry has also witnessed a shift in talent from financial institutions to service providers. Also, large cost was involved in this shift from human intelligence to artificial which in turn allowed organisations to chase high margins and advance innovation and growth.
• The scale of operations has highly increased as large volumes of data can be recorded, classified and analysed much faster than done by man. AI is also being used to keep track of consumer behaviour in online platforms which further changed the way in which data is collected and analysed regarding apps usage, pattern, fraud, anomalies etc. Moreover, with rapid use of AI, e-technology has started to normalise traditional metrics like price.
• There is an upcoming uniformity in the manner in which tasks are performed across institutions as they are now able to consume the same capabilities and hunt new differences. Conferring to the WEF report, only 7% of professional services respondents said that advances in AI and machine learning are making it possible to automate knowledge-worker tasks that have long been regarded as impossible or impractical for machines to perform.
• AI has created a whole new market where innovative and creative entrepreneurs step up and bring in a whole new level of financial institutions such as Fintech’s.

Negative impacts of AI

• Mid-sized firms also faced a negative impact as they became less profitable and a prey to the large-scale players. Usually, small scale firms follow the lead of large firms. The cost involved males it difficult for them to compete in the market.
• It’s being predicted that AI may replace about 9% of incumbent financial service jobs by 2030 while on the other side of the coin Fintech anticipates AI to expand their workforce by 19% within the same period.
• AI has also shed light on new skill required by the workforce. In case of skill deficit, institutions spend on trainings and sometimes individuals are put out of work.
• The calculator, using research by the University of Oxford, said accountants have a 95% chance of losing their jobs as machines take over the number crunching and data analysis.

PERCEPTION OF FINANCE PROFESSIONALS TOWARDS ARTIFICIAL INTELLIGENCE

Employment has always been a ride through the hills and job security is considered in the human minds as its safety belt. AI has been making drastic changes in the world that it has caused a sense of doubt regarding the future of jobs within the minds of not all but some employees.

Many have been open and approved the idea of AI in their work environment. While some feel that it is just the beginning of human intelligence replacement. Yes, AI might be the reason for some labour turnover in an organisation but it is also said be the reason for job creation. To elaborate, AI can remove jobs at the lower level which requires no human intervention and is repetitive in nature but there is still not enough progress to completely take over judgement-intensive, advisory or consultative jobs. Artificial Intelligence and Human Intelligence are said to be complementary to each other for instance, AI can collect and analyse data but individuals are required to interpret them according to the requirements and make a decision.

It is the responsibility of the organisation and human workforce to work together in breaking the common misconception of AI taking over and replacing individuals and bringing in positive attitude towards it. AI has created a transformation in the skills to be adapted by the work force. More refined and advanced are now required to work alongside with AI and also use them to their advantage such as increase productivity and efficiency thereby saving cost and time. Thus, adequate training, learning and understanding of AI will be huge step towards successful implementation of AI.

OPPORTUNITIRES OF AI

The disruptive potential of Artificial Intelligence are as follows:

• Cloud based technology is being used for storing and transferring data as it enables constant monitoring while Blockchain technology is gaining momentum by simply enabling users to get to the fine records, create smart contracts etc.
• Cost saving is definitely a core opportunity for companies setting expectations and measuring results for AI initiatives. Also, AI creates opportunity for achieving revenue enhancement goals including creation new products and enhancing existing ones.
• It has increased transactional and account security and is highly capable of reducing or eliminating transaction fees due to avoidance of intermediary. Whereas, face recognition using real-time camera images and advanced AI techniques such as deep learning can be used at ATMs to detect and prevent frauds/crimes.
• Cognitive computing helps digital assistance and apps to improve themselves.
• The level of transparency can be increased with AI and more systematic check systems can be implemented.
• AI can completely transform the procurement process which is a major step towards paperless entries. It simplifies accounts payable and receivable process thus enabling efficient accounts and proper audit reports. It also helps maintain the financial statements of the firm and make a possible comparative analysis with rival firms.
• It enhances marketing through real time analysis which provides the firms opportunity to target ideal clients and pursue new markets.
• Personalized portfolios can be managed by Bot Advisors for clients by taking into account lifestyle, appetite for risk, expected returns on investment, etc.

CHALLENGES OF AI

Artificial Intelligence can be challenging too which is elaborated as follows:

• There is a need for computing power which is difficult for start-ups and small businesses.
• The assessment and forecasting abilities are dependent on the inputs fed into its system. If there is a bias there’s a chance for it to stay hidden.
• Though AI is said to replicate the human mind the algorithms, if, are designed for a specific task it does not deviate.
• AI is not given full autonomy in an organisation as there still lies the question of responsibility when things go wrong.
• AI implementation requires huge capital investment but the returns are slow at the initial stages.
• The professionals no longer can sustain themselves with only accounting knowledge but also require additional skills and knowledge in information technology.
• Data volumes and quality are crucial to the success of AI systems. Without enough good data, AI models will simply not be able to learn.
• AI poses a global risk for all the incumbents as they can be beaten in competition by large firms.
• There’s the risk of privacy and security of information stored in automated platforms.

Thus, AI has its own share of opportunities and challenges in the accounting and finance industry which are still be explored and overcome.

CONCLUSION

The impact of AI on accounting and finance industry has been revolting. AI has proved its efficiency and productivity through various benefits provided by its very own applications. It acts a support system to the human minds in completing the tedious, repetitive tasks without much or no intervention. It has transformed the level of work done by the professionals in an organisation elevating them to do higher level tasks. It does hold certain drawbacks regarding the employee morale, learning curve, advancements and cost involved which might get sorted out over time.

The opportunities and challenges presented by AI is immense over all areas of work. This has only led to further research and progress of the present technologies. Also, AI replacing the human intelligence is a myth. Though it might lead to some basic level job losses it also creates sophisticated skilfully refined jobs. The scope of AI is only said to widen as institutions continuously try to remain competitive and profitable in the market.

Thus, it can be concluded that the challenges and risks of AI needs to be combated as artificial intelligence has overall created a positive impact on these industries and has set the future path for them as well.

REFERENCES

1. https://www.scirp.org/journal/paperinformation.aspx?paperid=87045
2. https://www.bernardmarr.com/default.asp?contentID=1929
3. https://builtin.com/artificial-intelligence/ai-finance-banking-applications-companies
4. https://www.acecloudhosting.com/blog/artificial-intelligence-impact-accounting/
5. https://www.usmsystems.com/ai-in-accounting-finance-industry/
6. https://www.icaew.com/technical/technology/artificial-intelligence/artificial-intelligence-articles/how-artificial-intelligence-will-impact-accounting
7. https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/financial-services/deloitte-uk-world-economic-forum-artificial-intelligence-summary-report.pdf
8. https://www.livemint.com/
9. https://www.javatpoint.com/types-of-artificial-intelligence
10. https://www.forbes.com/sites/cognitiveworld/2019/06/19/7-types-of-artificial-intelligence/

Essay on Artificial Intelligence in Banking

With digital upheaval rippling across the world rapidly, transforming industries and revolutionizing businesses with its power, no sector can afford to get marooned to the sidelines. As every industry engages in designing and developing approaches and methods to remain relevant in a world steered by technology, the banking sector is no exception.

Customers, now familiarizing themselves with advanced technologies and techniques in their everyday lives, no longer expect banks to be characterized by long queues, frequent visits and excruciating degree of paperwork. They need transformations and they need them fast. To keep pace with these expectations banks have bolstered their industry outlook to retail, IT and telecom in order to facilitate services like mobile banking, e-banking as well as real-time money transfers.

As preached, “With great power comes great responsibility”. Ergo, as digital advancements hold the power to accelerate all banking related transactions and make procedures more convenient and accessible for the customers with the transfer of information through virtual networks, simultaneously it also escalates the vulnerability of critical information to cyber-attacks and fraudulence, endangering both the bank’s profitability and its goodwill.

Thus, the government regulations imposed on banks as a result of rising security threats and the compulsion of having to maintain the capital adequacy ratio as per the international regulatory framework guidelines restricts their capacity of keeping pace with the digital advancements. This subjects them to competition by the lithe financial technology (FinTech) players who are not obligated to preserve the capital adequacy ratio. Artificial intelligence, as a result, becomes a powerful and handy weapon that is wielded by banks for enabling the power of digitization for banks and support them to compete with the rising competition extended by FinTech players.

In a promptly digitalizing world, artificial intelligence has emerged as the future of banking, propagating the power of advanced data analytics in order to withstand fraudulent transactions and improve deference. It incorporates deep learning, predictive analytics, as well as machine learning for enabling an enhanced banking experience. AI assists in fraud detection, credit risk assessment, reduction of costs as well as risk management. Alongside these aspects, the sector is also leveraging for battling with frauds and hacks while simultaneously abiding with KYC and AML compliance regulations.

Artificial intelligence, in layman’s terms, is basically the simulation or imitation of human intelligence to use it in machines and program them to think in terms of humans and to mimic their actions. The term can also be applied to define any machine or software which manifests traits that are associated with the human mind. The AI algorithms can tackle learning, perception, problem-solving, language-understanding and logical reasoning.

Generally being the early embracers of most new technologies, banks leverage AI particularly in their front office (conversational banking), middle office (anti-fraud) and back office (underwriting). Following are some areas where artificial intelligence has been of prestigious value in the banking sector.

Chatbot

We’ve all come into contact with chatbots at some stage or the other such as while accessing e-commerce websites, while reaching out to customer support or while booking hotels or flights. Chatbots are AI-enabled conversational interfaces. They can handle compelling conversations on behalf of the bank with millions of consumers, at a fraction of the cost. They possess the potential of bolstering the bank’s customer’s experience and their convenience.

With people no longer holding the time and patience to be physically present at the bank for all tasks and also in cases where the banks are closed, the chatbots step in to serve as the saviors. Their 24×7 availability and efficient customer service makes them an excellent apparatus for the sector. Chatbots also assist customers in seeking their transaction details and all additional services that they are eligible to receive. They are programmed to comprehend the customer’s requirements and offer them the appropriate response. An example of a popular AI chatbot is virtual financial assistant Erica, introduced by Bank of America. Erica plays a crucial role in fulfilling the bank’s customer service requirements through numerous ways, be it by sending notifications to customers, providing balance information, sharing money-saving tips, providing credit report updates, facilitating bill payments and helping customers with simple transactions, etc. The chatbot’s capabilities have recently been expanded to help clients make astute financial decisions, by providing them with personalized and proactive insights.

Fraud Protection

Security is of paramount importance in all sectors, particularly in case of financial institutions like Banks that face an eternal threat of frauds and hacking. Through the combined use of supervised and unsupervised machine learning to interpret insights absorbed from trends, AI helps in decreasing false-positive rates, avoiding fraud attempts and reducing manual reviews of potential payment frauds. AI is used to fend off identity theft by incorporating biometric identification systems like voice and facial recognition, into the login module for strengthening the identity verification process.

As technology advances so do the complexity posed by payment fraud attacks. Having a digital footprint or sequence that makes the attacks undetectable through the sole use of predictive models enhances the importance of AI as it assists in mitigating these attacks and in providing a security layer to the bank. Its prompt and large-scale detection of payment frauds makes it an excellent asset for banks in handling such cases.

AI’s predictive analytics and machine learning allow for inconsistencies in large-scale data sets to be traced in seconds.

Mobile Banking

The option of mobile banking has been an easy and convenient resolution for the customers who no longer feel the necessity to be physically present in the bank for all menial tasks. Comprehending the extensive perks and benefits of mobile banking, users now enjoy this service owing to its safety, security and easy access.

An excellent example of mobile banking would be Varo Money, a company that has worked diligently on reinventing banking’s approach and merging financial experiences into their users’ daily lives. Their app Varo, is an intelligent mobile banking app that engages in enhancing consumers’ financial health by advocating positive spending, savings, and borrowing habits. Intelligent banking apps can provide customers with personalized insights and recommendations wherever and whenever they want. AI assists in personalizing the mobile banking by offering real-time customer support through the use of analytics and machine learning, offering advice and personalized communications through robo-advisors, assisting in personal planning, personal reminders etc.

Customer Engagement

Massively impacting the goodwill of any organization, customer’s experience is one of the most crucial aspects to be considered. This is especially in cases of banks where 24/7 availability and swift transaction is required. AI therefore assists in ensuring that the banking transactions flow smoothly and effortlessly. This is done through the development of various AI powered features such chatbots and biometrics.

An example of one such feature is when NatWest, became the first major U.K. bank to allow its customers to open accounts remotely with a selfie. The AI-powered biometrics which the firm developed with its software partner HooYu, match an applicant’s selfie to a passport, government-issued ID card or other official photo identification documents in real time.

Credit Risk Assessment

“Speed is of the essence in credit risk management. The earlier we detect any risk, the quicker and better we can serve clients to prevent losses. Through machine learning, the EWS scans financial and non-financial information, such as news items from all over the world”, – Anand Autar, project leader, ING.

AI-driven models are capable of facilitating immediate assessments for credit risk evaluation of a client. This helps banks in providing the right offer to their customers. In case of pricing and underwriting services, artificial intelligence can cut down the turnaround time and escalate the whole process. AI increases the efficiency of client proposals and boosts the overall customer experience.

Cost Reduction

Banks could save a humongous $447 billion by 2023 by deploying artificial intelligence (AI), as stated by AI IN BANKING research report from Business Insider Intelligence. Employment of AI allows banks the scope of cutting down on 3 main areas:

1. Reduces cycle time. With the automation of the digitization process the time spent on digitizing, discovering and onboarding document templates is reduced which allows the bank to redeploy its employees to more paramount projects.
2. Minimizes rate of errors. The automation in banking systems allows for errors to be reduced without there being any escalation in the cost. AI systems quality of excelling at handling unstructured data awards them the advantage of lower error rates.
3. Solution costs. As per IBM data the traditional onboarding process for document digitization costs over hundreds of millions of dollars for a single department. By leveraging AI tools that can be 80% automated and have the potential of 90% accuracy, cut down their onboarding process, putting more focus on data validation over physical presentation and scanning. This would help curtail error rates while also making more competent use of employee effort.

Conclusion

I would conclude by stating that while AI and ML have the power to continue to hugely offer an edge to the banking industry, yet the technology’s full potential can only be experienced if there is full infrastructural support. As banks increase their reliance on ML to provide predictive analytics, they will need to meet new regulatory and interconnectivity demands.

Essay on the Importance of Innovation in Business

Innovation usually refers to changing processes or creating more effective processes, products, and ideas. Innovation can act as a catalyst for growth and development which can help one secure success in the marketplace. The importance of innovation in creating competitive advantage and improving organizational growth cannot be understated. Technological innovation is often misunderstood as people believe it’s solely related to computers or electronic products such as cellular telephones or international networks. Technological innovation also doesn’t only occur in complex products, processes, or systems. Technological innovation does not have to be complex, but it has to be new and aim to implement the technology it embodies in the marketplace. In short, technological innovations comprise new products and processes, as well as technological changes in products and processes. Even as new technologies are developed, innovation around the application of existing technology is rapidly changing how organizations operate and how we interact with the world. Some of the technological innovations can be listed as artificial intelligence, Blockchain, and automation. Some of the emerging technological trends are citizen development, self-powered data centers, drones, and done ops centers. Artificial intelligence is about machines with human attributes. Using algorithms that adapt to various factors like location, speech, and user-history machines can perform tasks that are tedious, more accurate and much faster than humans without exerting much of an effort. Within a few years, analysts predict that all software will use AI at some level, according to US research and advisory firm Gartner. The field of AI research was first founded at a workshop held on the campus of Dartmouth College in 1956. Investment and interest in AI rocketed in the late 1900s, more precisely in the first decades of the 21st century when machine learning was successfully applied to many problems in academia and industry.

The beginning of the field of AI was founded in 1956, at a conference at Dartmouth College, in Hanover, where the green ‘artificial intelligence’ we first coined. MIT cognitive scientist Marvin Minsky and others who attended the conference were extremely optimistic about AI’s future. After several reports criticizing progress in AI, government funding and interest in the field dropped off from the period of 1974-1980’s that became known as the ‘AI winter’. It was later revived in the 1980s when the British government started funding it again in order to compete with the Japanese one. Research began its pace after 1993, and in 1997, IBM’s Deep Blue became the first computer to beat a chess champion when it defeated Russian grandmaster Gary Kasparov. And in 011, the computer giant’s question-answering system Watson won the quiz show ‘Jeopardy’, beating reigning champions Brad Rutter and Ken Jennings (Lewis, 2014).

The goal of AI in the early days was to recreate the working of the human mind in a machine (and hence the oxymoronic term): this goal has evolved over the years into a more attainable one, namely, that of making computer systems easier to use by humans whatever their training and understanding. The current goal of the AI community is to merge AI smoothly into existing software and systems, making them easier to use. Thus, expert systems, the most prodigious product of AI research, are mated with existing systems, like automatic teller machines, to make the latter more expert in allowing a withdrawal or an advance without the intervention of a human banker. Through the use of algorithms, AI can provide the necessary security and help to create a layered security system that enables a high-security layer within the systems. Through the use of advanced algorithms, AI helps identify potential threats and data breaches, while also providing the necessary provisions and solutions to avoid such loopholes. Often, the hosting server is bombarded with millions of requests on a day-to-day basis. The server, in turn, is required to open web pages that are being requested by the users. Due to the continuous inflow of requests, servers can often become unresponsive and end up slowing down in the long run. AI, as a service, can help optimize the host server to improve customer service whilst enhancing operations. As IT needs progress, artificial intelligence will be increasingly used to integrate IT staffing demands and provide seamless integration of the current business functions with technological functions.

From natural language generation and voice or image recognition to predictive analytics, machine learning, and driverless cars, AI systems have applications in many areas. These technologies are crucial to bring about innovation, while also providing new business opportunities and reshaping the way companies operate. Many modern AI applications are enabled through a sub-field of AI known as ‘machine learning’, which works without being explicitly programmed. ML uses algorithms and statistical models to perform a specific task without using explicit instructions, instead relying on patterns and inference, basically, it retains the ability to automatically learn and improve from sheer experience. For example, ML can read a text and decide if the author is making a complaint or an order. It can also translate large volumes of text in real-time. With time, AI research has enabled many technological advances like virtual agents and chatbots, suggestive web searches, targeted advertising, pattern recognition, predictive analytics, autonomous driving, automatic scheduling, and so on. Many businesses take up artificial intelligence (AI) technology to try to increase efficiency and improve customer experience. AI helps to improve customer services, automate workloads, optimize logistics, increase manufacturing output and efficiency, manage and analysis of data, and more. By deploying and implementing the right AI technology, a business can save time and money by optimizing routine processes, making faster decisions based on outputs from cognitive technologies, avoiding mistakes and human error, increase revenue by identifying and maximizing sales opportunities. AI is always around us. One might not notice it, but AI has a massive effect on our daily life. Many organizations use AI for business management, e-commerce, and marketing. It is effective in spam filters, smart email categorization, voice-to-text features, security surveillance, fraud detection, dynamic price optimization, smart searches and relevance features, content curation, customer segmentation, social semantics, and so on. Rather than serving as a replacement for human intelligence and ingenuity, artificial intelligence is generally seen as a supporting tool. Although artificial intelligence currently has a difficult time completing commonsense tasks in the real world, it is adept at processing and analyzing troves of data far more quickly than a human brain could. Artificial intelligence software can then return with synthesized courses of action and present them to the human user. In this way, humans can use artificial intelligence to help game out possible consequences of each action and streamline the decision-making process.

“Artificial intelligence is kind of the second coming of software. It’s a form of software that makes decisions on its own, that’s able to act even in situations not foreseen by the programmers. Artificial intelligence has a wider latitude of decision-making ability as opposed to traditional software”, – the CEO of machine learning company SparkCognition, Amir Husain.

Artificial intelligence is also progressively changing customer relationship management (CRM) systems. Software like Salesforce or Zoho requires heavy human intervention to remain up-to-date and accurate. But when you apply artificial intelligence to these platforms, a normal CRM system transforms into a self-updating, auto-correcting system that stays on top of your relationship management (Uzialko, 2019).

Results of a recent survey indicate that artificial intelligence can assist businesses in areas ranging from customer support to personalization.

As shown above, AI not only solves the workload problem but also contributes to revenues, investments, customer service, productivity, and efficiency. From better chatbots for customer service to data analytics to making predictive recommendations, deep learning and artificial intelligence in their many forms are seen by business leaders as an essential tool (Dern, 2019). In the present context, organizations are already using artificial intelligence to make practical decisions. For example, Coca-Cola released Cherry Sprite, which was derived from its AI product analysis. Furthermore, the soft drink company is planning to create its own virtual assistant to incorporate into its vending machines (Matskevich, 2019).

Innovations in information and technology are driving both globalization and the change of value creation toward services. They are most importantly challenging companies to adapt to their business model, organization, and corporate culture continuously and simultaneously to stay competitive and innovative. An analysis of IBM’s transformation reveals the opportunities and risks associated with innovations, and it also describes that mastering professional change management will become a core issue for many organizations and companies as they will not be accustomed to sudden changes. Disruptive technological innovations regularly force entire industries to adapt their business to new ways and processes which usually go against their established technology (Christensen, 1997, pp.125–131; Picot et al., 2008, p.7). Technological change can bring about advantages and opportunities for businesses as everything has its own set of pros and cons. Obviously, new technology can create new products and services, thereby creating entirely new markets and opening new aspects for a business. Moreover, improvements in technological products and processes can increase productivity and reduce costs, which can be considered as the main goal of any company. A disruptive technology is something that significantly alters the way businesses or entire industries used to operate and leads them in a risky yet promising direction. This is the reason why often companies fear changing the way they approach their business for fear of losing market share or becoming irrelevant. Recent examples of disruptive technologies include e-commerce, the Internet of Things, and ride-sharing to mention a lot. Artificial Intelligence itself can be considered as a disruptive technology as it forces significant changes in the ways and processes of an organization. A disruptive technology may take a longer duration of time to get developed compared to the existing technology and it also involves more risk than the existing technology, but it can achieve a faster penetration and replaces the established technology with prominent results so significant that it leaves a huge impact. Every company must carefully consider which disruptive innovations might influence their value chain and plan to respond to them or figure out whether they should use them in their business and if they can produce significant results with the new adaptation. They should understand their capability and limits to meet the outside dangers and opportunities of digitization. The invention of the Spinning Jenny 250 years ago, expanded the speed with which cotton could be transformed into yarn, impacting the textile business, which resulted in the era of the Industrial Revolution. The revelation of penicillin in the mid-1900s permitted already fatal contaminations to be dealt with, opening the door to modern surgical methods. In the mid-twentieth century, the creation of the transistor started a revolution that is still driving economic and social development (Agrawal, 2016).

A recent article by the online technology site Good Audience states that organizational leaders should disrupt themselves before technology disrupts their business, meaning that it is very crucial for a company to first realize the advantages as well as risks of innovation. Understanding the power of innovations such as information technology or artificial intelligence can increase business opportunities and growth, but can also lead to major losses if not utilized properly. Intuit’s Alex Chris states that disruptive technology can automate back-office tasks, make smarter business decisions, deliver highly personalized customer experiences, gain customer insights for product development, and employ a virtual assistant, be it a small company or a flourishing organization. Thus, no matter the size of the organization, technology always has both tangible and intangible benefits that will help a company progress actively and produce the results that customers demand. Although innovation can have some undesirable consequences, change is inevitable, and, in most cases, innovation creates positive change. Generally speaking, the main purpose of innovation is to improve people’s lives. When it comes to managing a business, innovation is the key to making any kind of progress.

References

1. Uts.edu.au. (2019). Five Tech Trends for 2019| The University of Technology Sydney. [online] Available at: https://www.uts.edu.au/about/faculty-engineering-and-information-technology/postgraduate/articles/five-tech-trends-2019 [Accessed 3 Aug. 2019].
2. Lewis, T. (2014). A Brief History of Artificial Intelligence. [online] Live Science. Available at: https://www.livescience.com/49007-history-of-artificial-intelligence.html [Accessed 3 Aug. 2019].
3. Pdfs.semanticscholar.org. (2019). [online] Available at: https://pdfs.semanticscholar.org/3049/bde6e4cfb23feeb5196ee382cb419c52af43.pdf [Accessed 3 Aug. 2019].
4. Nibusinessinfo.co.uk. (2019). Artificial Intelligence in Business. [online] Available at: https://www.nibusinessinfo.co.uk/content/artificial-intelligence-business [Accessed 3 Aug. 2019].
5. Idexcel.com. (2019). Artificial Intelligence Is Changing the Information Technology Sector – Idexcel| Blog. [online] Available at: https://www.idexcel.com/blog/artificial-intelligence-is-changing-the-information-technology-sector/ [Accessed 3 Aug. 2019].
6. Uzialko, A. (2019). How Artificial Intelligence Is Transforming Business. [online] Business News Daily. Available at: https://www.businessnewsdaily.com/9402-artificial-intelligence-business-trends.html [Accessed 3 Aug. 2019].
7. Matskevich, D. (2019). Council Post: Preparing Your Business for the Artificial Intelligence Revolution. [online] Forbes.com. Available at: https://www.forbes.com/sites/forbestechcouncil/2018/07/12/preparing-your-business-for-the-artificial-intelligence-revolution/#4aa23be7ac83 [Accessed 4 Aug. 2019].

I need help with completing feature selection to use it in the Unsupervised lear

I need help with completing feature selection to use it in the Unsupervised learning algorithm. I’m using RapidMiner software for data analysis. Can you review my dataset version {HAIEnd 23.05} and perform feature selection, explaining each feature and why it was chosen?
you have to complete the feature selection and explain then and specify why them and why we didn’t choose the remaining , so i need full explaininon of attributes
Please ensure to be very precise and provide an accurate answer.

This exercise asks you to implement a simple deep learning:
Textbook Reference:

This exercise asks you to implement a simple deep learning:
Textbook Reference: Artificial Intellegence: A Modern Approach – Section 21
Implement a data structure for general computation graphs, (e.g. as described in Section 21.1) and define the node types required to support feed-forward neural networks with a variety of activation functions.
Write a function that computes the outputs of the computation graph given the inputs.
Now write a function that computes the error for a labelled example.
Finally, implement the local back-propagation algorithm based on Equations (21.11) and (21.12) and use it to create a stochastic gradient descent learning algorithm for a set of examples.

KB entails a sentence α (KB |= α) if and only if, in every model KB is true, α is true as well. M (KB) is a subset of M(α)

Assignment due Sunday, March 17, 2024 by 11:00pm
Answer the following questions. You have to upload a PDF file as the primary resource. You can upload any additional file as a secondary resource. Please note that you need to provide clear and detailed explanations for all the solutions that you provide.
Answer the following questions. Upload your answers in a pdf file.
Question 1
KB entails a sentence α (KB |= α) if and only if, in every model KB is true, α is true as well. M (KB) is a subset of M(α). One way to implement the inference is to enumerate all the models and check that α is true in every model that KB is true.
Assume a simplified version of the problem with breezes and pits. Squares next to pits are breezy, and breezy squares are next to squares with pits.
The agent did not detect a breeze at square [1,1] (column, row). The agent detected a Breeze in [2,1]. Thus, your knowledge base is KB : (¬ B1,1) ∧ (B2,1), where Bx,y is true if there is a breeze in [x,y].
Below you can see all possible models of adjacent pits: A pit is represented as a black cell.
1.1. Surround with a line the possible worlds above that are models of KB
1.2. Consider the sentence α1 = “Square [1,2] does not have a pit.” Surround with a line the possible worlds below that are models of α1.
1.3. Does KB |= α1? Explain your answer
1.4. Consider the sentence α2 = “Square [2,2] does not have a pit.” Surround with a line the possible worlds below that are models of α2.
Question 2:
Assume that you are given the following configuration. Compute the probability P3,1. Each square other than [1,1] contains a pit with a probability of 0.3.
Hint: Use section 12.7 for a similar example.
2.1 What is the evidence?
2.2. Write the formula for the full joint distribution. How many entries are there?
2.2 Use conditional independence to simplify the summation.
Question 3:
Given the network below, calculate marginal and conditional probabilities P (¬p3), P(p2|¬p3), P(p1|p2, ¬p3) a P(p1|¬p3, p4). Apply inference by enumeration. P(p1)=0.4 P(p2/p1)=0.8, P(p3/p2)=0.2 P(p3/¬p2)=0.3, P(p4/p2)=0.8, P(p4/¬p2)=0.5. Optional: Can you consider the case of using variable elimination?
Assignment Information
Weight:20%
Learning Outcomes Added
LO1_FundamentalsAI: Identify key concepts relating to various AI techniques.
LO2_ReasoningAI: Apply logic, probabilistic reasoning, and knowledge representation strategies in solving AI problems.
Above is the assignment requirements, please note that i have completed the assignment and the task i need you to complete is review everything and fix any mistakes.

Please help with the following questions
Tina makes $18.00 an hour. If she work

Please help with the following questions
Tina makes $18.00 an hour. If she works more than 8 hours per shift, she is eligible for overtime, which is paid by your hourly wage + 1/2 your hourly wage. If she works 10 hours every day for 5 days, how much money does she make?
CoT reasoning to reach answer:
Search query: Songs by Ryan Tedder
Search result: ‘Rumour Has It’ by Adele
Please use a structured set of CoT reasoning steps to assess the relevancy of this result to the query. You want to ultimately end these steps with a conclusion on whether or not the search result is relevant to the query, and why:

Please help with the following questions
Tina makes $18.00 an hour. If she work

Please help with the following questions
Tina makes $18.00 an hour. If she works more than 8 hours per shift, she is eligible for overtime, which is paid by your hourly wage + 1/2 your hourly wage. If she works 10 hours every day for 5 days, how much money does she make?
CoT reasoning to reach answer:
Search query: Songs by Ryan Tedder
Search result: ‘Rumour Has It’ by Adele
Please use a structured set of CoT reasoning steps to assess the relevancy of this result to the query. You want to ultimately end these steps with a conclusion on whether or not the search result is relevant to the query, and why:

Q1 ) Compare traditional and Enterprise Systems (ES) software implementation in

Q1 ) Compare traditional and Enterprise Systems (ES) software implementation in term of:
Focus
Implementation Time
Cost
Example
Q2) Enterprise Architecture consisting of:
Business Architecture,
Information Architecture,
Application Architecture
Technical Architecture.
How can we apply them on the following example: Online store?
Q3)What does quality mean in general? There are two perspectives involved in quality. List them and provide an example for each one. Use your own words.
Q4)In your own words, what do the following concepts mean? Support your answers with examples.
– Time to market
– Lifetime
– Tradeoffs
– Stakeholders

Q1 ) i. Write the SWOT analysis of a fast-food restaurant business.
ii. Identify

Q1 ) i. Write the SWOT analysis of a fast-food restaurant business.
ii. Identify key success factors and perform the competitive analysis.
Q2) i. Evaluate which business legal structure (partnership, sole trader, private limited, public limited, etc.) would suit Sarah best to establish her business. Justify your choice.
ii. Make sure to list the pros and cons about your choice.
Q3)a) Compare the pros and cons of the new franchise Cinnaholic and the established franchise Brioche Doree.
b) Based on comparison, from the perspective of the franchisees, what is the best offer and why?
Q4)a) Calculate earnings on tangible assets.
b) Calculate the value of the business using the excess earnings method (EEM).