automation

AI in business operations

The Role of AI in Streamlining Business Operations

How big of a change will AI in business operations affect me? Everyone is thinking about it—even you. But not many have an answer to these questions. It’s uncharted territory for many of us especially since AI’s recent boom caused quite a stir. Just two years ago, ChatGPT was released alongside AI-made art, software designers, and more. Since then the impact of AI in business operations has slowly been noticeable for many. However, each person with each specialty has their own experiences with AI. Below you’ll find the changes caused by the appearance of artificial intelligence in business. Examples of each profession teach us the different changes AI can give (regardless if it’s good or bad for the employee.) What is Artificial Intelligence? There’s a step we have to take first to learn about AI in business operations. Before we dive into all the nitty-gritty details we should first discuss what artificial intelligence is. Contrary to popular belief, artificial intelligence isn’t just software-related. People think that AI has become a big challenge only just recently. The truth is that we’ve been using AI far longer than what everyone else thinks. AI technologies have been around since the 1900s and only matured in the 1950s.  Artificial Intelligence is a method of computer science that imitates the human brain’s capacity for creating, solving, and overall intelligence. The mimicking method of artificial intelligence to copy human procedures remains imperfect to this day. However, it can now generate some interesting results that have caused debates and delays to professions and businesses. 5 Use of Artificial Intelligence in Business Operations Now, it’s time to learn the role of AI in business operations. Take note that these are just a few examples. However, these examples may give you a general idea of what AI has in store for your profession. AI in Data Management AI in business operations, such as data management, is a beneficial response to the increasing challenge of cybersecurity. The digital age has caused an influx of cybercriminals dedicated to breaching data, which is something AI in data management helps prevent. Not only that, artificial intelligence can also mimic some menial data science tasks. These menial tasks include organisation, data gathering, and optimisation. This makes a data scientist’s job easier, as they can focus on the other more specialised tasks of their trade. AI in Customer Service There’s a lot of debate on the survivability of customer service representatives because of the rise of AI in business operations. Unfortunately for many, there are fact-based backings regarding AI in customer service, which shows that some jobs will become obsolete in the future. However, customer service won’t completely be replaced by artificial intelligence. What AI in customer service cannot replicate is the human empathy and understanding of each consumer’s needs. Instead, it may become an assistant and partner for customer service operations. Especially with the high demands of multiple consumers. AI in customer service will instead take care of the menial tasks such as data entry for customer service. It can also organise complaints and inquiries in categories.  AI in Supply Chain Management The benefits of artificial intelligence in business aren’t just as partners in specialties or careers. AI in business operations such as supply chain management can decrease the time consumed by processing operations. How does it do that? It’s simple. AI in supply chain management assists through the optimisation of routes with workflows, automating tasks, and improvement of delivery.  The errors in supply chain management come from shipping, organisation, and an imbalance between logistics. That’s why AI serves as a critical tool to maintain seamless operations by creating optimised patterns for more cost-effective supply management. Long gone are the days when warehouse-cargo-distribution centres would incur mixups and confusion between deliveries. That is, as long as you know how to properly balance AI with human management. AI in Human Resources Many people wonder about the role of AI in business operations. None more so than those working in human resources. Contrary to popular belief, human resources aren’t a big cause of concern regarding job replacement by AI. Instead, AI in human resources helps HR with recruitment and management activities by organising and supporting HR’s administrative and operational processing. Compared to other professions in business, AI is still slightly in the dark concerning its effects on human resources. Further discussions and research are needed to provide accurate information on AI’s potential in HR and its possible effects. AI in Marketing and Sales Unlike other AI in business operations, marketing and sales have adopted its support for a long time. Contrary to popular belief, search engines are self-service resources that allow you to sort out relevant information regarding your intent using AI through algorithms and machine learning. This doesn’t necessarily mean there aren’t any new changes. Recently, generative AI has become a resource for consumers in transactional-based searches. That’s where marketing fits in. With the help of SEO specialists and content writers, digital marketing has begun its ascent into a necessity for a business’s survival. This time AI’s generative capabilities have given these specialists an advantage to steer their content into transactional-based information, at the very least, those within their niche. The same goes for sales as well, AI helps track note-taking during meetings, speeds up researching, and even analysing calls between clients. With the help of AI, salespeople can even predict potential market leads, and gain prospects based on search intent. Future of AI in Business Operations The impact of AI on business operations is unavoidable. Times have changed and it’s our job as business operators to flexibly manoeuvre ourselves to go along with its flow. It’s expected that AI will increase its supporting capabilities to numerous professions and businesses.  Whether it will replace certain careers is still in debate. What is considered a fact is that any impact AI has in the near future will be solely supportive of specialists in their field rather than replacements.  Its seamless capabilities will guarantee smoother transitions

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AI and smart automation

Generative AI and Smart Automation in Cybersecurity

In the ever-evolving landscape of the IT industry, few advancements have gained as much attention and intrigue as generative artificial intelligence (AI). With its emergence onto the scene in 2023, generative AI swiftly captivated industries, revolutionising almost everything—from content creation to healthcare diagnostics. However, one area that stands to benefit profoundly from this groundbreaking technology is cybersecurity: The combination of AI and smart automation. We interviewed Flexisource IT’s Compliance Officer, Earvin Camanian, to talk about AI, smart automation, and some of its threats that we should know about. What can AI and smart automation mean for cybersecurity in 2024? AI and smart automation had a huge impact on operational processes and cost initiatives for organisations. These revolutionary solutions enable organisations to work efficiently and swiftly, producing good-quality products and services minimising defects and delays. Likewise, AI and smart automation can help organisations and even people make their lives more convenient. However, “convenience leads to complacency and negligence” because we tend to be dependent on AI and smart automation. The growing number of AI tools especially “generative AI,” is growing rapidly and cybercriminals use that opportunity to victimise users. Hence, cybersecurity professionals will come into play to ensure a product or solution has the required security controls following industry standards to mitigate risk and reduce harm to users, particularly on AI. This is overwhelming work for cybersecurity professionals these days, knowing there is a limited number of cybersecurity professionals globally. It adds more problems because not all AI providers are investing in security, for they focus more on profit. Some are even used for illegal activities, portraying as a legitimate AI provider to steal data from users. What are the critical threats from the growing use of AI tools? The critical threats from the growing use of AI tools are: Data Breach As AI tools become more prevalent, the risk of data breaches increases. These tools often handle vast amounts of sensitive information, making them attractive targets for cybercriminals seeking to exploit vulnerabilities and gain unauthorised access to data. Identity Theft With the growing sophistication of AI algorithms, cybercriminals can use AI-powered techniques to steal personal information and perpetrate identity theft at scale. This can lead to financial losses, reputational damage, and emotional distress for affected individuals. Deep Fakes AI-powered deep fake technology enables the creation of highly convincing fake videos and audio recordings. Misuse of this technology can lead to the spread of disinformation, manipulation of public opinion, and damage to the credibility of individuals and institutions. Automated Weapon Systems The development and deployment of AI-driven automated weapon systems raise ethical concerns and risks of unintended consequences. These systems have the potential to autonomously identify and engage targets, leading to civilian casualties, escalation of conflicts, and challenges in maintaining accountability and compliance with international laws. Privacy Violations AI tools often rely on large datasets containing personal information, raising concerns about privacy violations. Unauthorised access to or misuse of these datasets can result in the exposure of sensitive personal information, erosion of privacy rights, and loss of trust in institutions that handle such data. Loss of Control The increasing reliance on AI tools in critical systems and decision-making processes raises concerns about the loss of human control. Errors or biases in AI algorithms can have significant consequences, leading to unintended outcomes, lack of accountability, and challenges in understanding or rectifying algorithmic decisions.  Social Manipulation AI algorithms can be used to manipulate social media platforms, online discourse, and public opinion. This manipulation can take various forms, including the spread of misinformation, polarization of communities, and amplification of extremist ideologies, leading to social unrest and erosion of democratic principles. Techno-dependent Humans Over-reliance on AI tools can lead to techno-dependence, where humans become increasingly reliant on technology for decision-making, problem-solving, and daily tasks. This dependence can diminish critical thinking skills, creativity, and human autonomy, posing risks to individual well-being and societal resilience. What other developments will continue to trend in cybersecurity in 2024? Industry standards such as NIST, ISO27001, etc. are painstakingly working to address the growing concern and issues related to AI. They recently released a new version (NIST Cybersecurity Framework v 2.0 and ISO27001: 2022 version) so that organisations can assess their security posture for any gaps within their network. This is to make sure that the level of security has reached an acceptable level. Another thing is new robust security solutions or products are going to be released by some security providers in response to AI such as data loss prevention and other related defensive measures to protect the identity of users. There is also an ongoing project where AI is also going to be used for Cybersecurity. This is something that we are anticipating to see how this new solution will work in our profession. How should organisations address the cybersecurity challenges in 2024? Step 1: For organisations, conduct a Risk Assessment of their IT infrastructure, Assets, Physical Security, and People. They need to identify the risks that could damage the organisation’s reputation and business operation. Once they identify a risk, create a treatment plan to mitigate and avoid transferring the risk. Senior management must consider their risk tolerance to make sure each identified risk does not hamper their business functions. Step 2: The second step is to develop information security, data privacy, and cybersecurity policies and procedures to enforce and execute security measures based on management objectives, industry standards, and legal and regulatory requirements. Step 3: Invest in information security training for employees to develop awareness of how they will act or respond to a security incident. A good example is “Phished Academy,” which will train employees on how to identify a phishing email. Step 4: Invest in IT security solutions such as Identity Access Management, Data Loss Prevention, Web filtering, SIEM, FIM, Vulnerability Assessment/ Penetrations Testing, and Security Operations Centre (SOC) apart from AV, firewall, and other related security solutions to protect the organisation’s internal network. Step 5: Lastly, hire a cybersecurity professional to provide you with

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