How is AI changing the way we work?
The advances in Artificial Intelligence (AI) have made an incredible impact on the way industries and businesses operate. Many experts say that AI brings positive changes such as enhanced efficiency and productivity but many people still fear that AI will steal their jobs. Goldman Sachs reported that AI could replace 300 million full-time jobs but will also lead to new jobs and a productivity boom with a 7% increase in global GDP.
Many businesses now use AI tools. A McKinsey Global Institute study reported that by 2030, 70% of companies will have adopted at least one type of AI technology.
In this blog, we will explore:
- The main ways on how AI is changing the way we work
- How AI has impacted business industries and
- Ways to improve your AI skills.
What is AI?
AI is the ability of a computer system to perform tasks that typically require human intelligence, such as learning, reasoning and decision-making.
The main ways that AI is changing the way we work
1. Automation of repetitive tasks
Some roles are burdened with repetitive and time-consuming tasks such as data entry, counting inventory or formatting data in a template. AI automation which combines Natural Language Processing (NLP), Robotic Process Optimisation (RPA), and Machine Learning algorithms can perform these tasks (without the help of people) by following predefined rules and evolving when new data is entered.
NLP algorithms help systems understand and generate human language (e.g. chatbots, Generative AI), RPA imitate human actions to perform repetitive tasks (e.g. robotic arm on an assembly line) and Machine Learning models are trained on data and can identify patterns and make predictions.
AI can complete repetitive tasks at a faster rate and provide insights to help you make better business decisions. This gives you more time to spend on more important projects, save on labour costs, increase employee efficiency and minimise errors.
Real-world examples
Amazon uses AI automation in fulfilment centres to detect damaged goods. Trained on millions of images, AI flags imperfect items to be assessed. Instead of being delivered to the customer, these items can be donated or reused.
Commonwealth Bank of Australia (CBA), one of Australia’s biggest banks, launched their chatbot named Ceba in 2018. It is available 24 hours a day and can do more than 200 banking tasks in real-time including helping customers pay bills and open new accounts. This gives CBA’s employees time to address more complex customer enquiries.
2. Better customer engagement
In a highly competitive market, it is important that every customer's experience is positive. The key to better customer engagement is personalisation. AI-driven personalisation uses a customer’s preferences and behavioural data (e.g. browsing and purchasing history) to tailor product or service recommendations and marketing messages. For example, an online shop could have a ‘Customers also bought’ section or ‘Top sellers list’ to encourage people to add more items to their cart. Personalisation can be used for many communication channels including website content, emails, and social media.
By connecting with that they are looking for, AI-driven personalisation can improve customer engagement, satisfaction and loyalty which results in greater profitability and business growth.
Real-world examples
- With PayPal’s Smart Receipts, customers (after their purchase) will be emailed a receipt with a tracking order, a list of recommended products that they can buy next from the same brand and cash-back reward offers. PayPal uses AI to analyse customer behaviour data and web research to create these lists. This has helped their retail partners encourage repeat purchases.
- Netflix uses AI to personalise the list of movies and shows based on your individual viewing history and provide recommendations for your next viewing session.
3. Faster content creation
Generative AI (GenAI) such as ChatGPT has revolutionised the way we create content. With the right series of prompts, GenAI can instantly generate copy, images and videos. It can help you with research, new ideas, even computer program code.
GenAI tools are trained on large bodies of text from a variety of sources to produce relevant content at a fast rate. The results can be used as a starting point for you to create unique messages. Always check the facts GenAI generates with other reputable sites and ensure that the information you type into the tool is not confidential or sensitive as it will be collected and stored.
Real-world examples
Salesforce, the global leader in CRM, launched Einstein GPT in 2023 and it connects their client’s data to large language models to help generate personalised content across sales, service, marketing, commerce and IT at hyperscale. Einstein GPT adapts to changing customer information and needs in real-time.
Adobe, the Software-as-a-Service (SaaS) business, has integrated GenAI features across its Creative Cloud suite of tools. For example, Adobe Firefly can generate images based on prompts (similar to DALL-E and Midjourney) and Photoshop’s AI tools help users create or edit images in less time.
4. Quick and insightful analysis of big data
With the fast adoption of digital technology, businesses now have access to vast amounts of data. The insights from big data are invaluable to helping leaders make strategic business decisions.
AI systems can quickly and accurately analyse and interpret large volumes of data, predict trends, draw conclusions and deliver actionable insights. The system evolves each time new data is entered into the system, resulting in more accurate predictions. People are needed to ensure the accuracy and quality of the data.
Real-world examples
Uber Eats wanted to ensure that food would stay warm upon delivery and minimise delivery times. They used Machine Learning algorithms to calculate a restaurant’s load at any time and how long it took to prepare each order to determine when a delivery person should come to pick it up. Drivers could pick up several orders instead of waiting. Uber Eats also uses AI to analyse their customers’ past purchasing behaviour to personalise their menu and make recommendations on their mobile app.
Amazon can predict what a person needs before they even know it by using predictive analysis (based on customer’s buying habits) and includes these recommendations in their communication to their customers.
How has AI impacted business industries?
Accounting
Many accounting firms are using AI to manage cash flow, categorise transactions (e.g. tax, payroll), process invoices and generate reports. AI can analyse large volumes of financial data to make predictions, identify trends and savings and detect input errors and suspicious transactions. You need to evaluate the accuracy of AI generated predictions and reports by benchmarking it against metrics and regulatory compliance.
Finance
Finance departments can use AI to process millions of data points and reports to:
- Generate insights for better forecasting, investment decisions and trading strategies in real-time
- Assess the ability of businesses and individuals to repay financing and the probability of insurance incidents
- Detect fraud by identifying unusual patterns and behaviours and
- Make product recommendations to customers based on their transaction history and spending patterns.
The accuracy of AI is dependent on reliable inputs. People are still required to ensure data quality, security, and adherence to financial regulations.
Banks and insurance teams are testing new chatbot models and using GenAI to convert their complex reports and manuals to be more user-friendly. GenAI can summarise financial metrics or reports and transform them into an engaging presentation for stakeholders.
AI automation of work processes gives more time for people to work on strategic projects. For example, software bots can deal with high-volume, repetitive tasks such as loan processing, claims management and compliance checks.
Business Analytics
AI business analytics tools offer automation of repetitive tasks by improving the speed of cleaning, organising and standardising large volumes of data. Machine Learning can perform predictive modelling (based on large and complex datasets) to identify patterns and trends, customer demands, potential risks and other business insights.
You will still need to assess the value of data sets to assure their quality and manage risks. AI will not remove the need for skilled people, but instead grow the capacity to turn more of your data into value.
Marketing
Sales and marketing departments are using AI tools for customer insights and content creation. AI can also automate and streamline work processes to give more time for marketing teams to work on creative strategies.
Here are several ways that AI is being used in Marketing:
- GenAI can produce copy, image and video content (e.g. scripts, brand statements) to be used across different communications channels.
- AI can automate email marketing and ad placements.
- AI algorithms can analyse and large volumes of customer data to help marketers create and tailor messages, ads and product recommendations.
- Machine Learning can analyse past campaign data to predict what content will perform best and suggest improvements.
- AI can improve SEO through keyword optimisation, content suggestions and technical adjustments.
Information Technology
Kash Rangan, Senior software analyst at Goldman Sachs (GS) Research reports that GenAI can simplify business workflows and give rise to a new generation of business applications. GenAI can find root causes, help write test cases, automate test scripts, and generate detailed reports.
AI can optimise data and maintain IT infrastructure as well as automate tasks such as performance monitoring, workload scheduling and data backups. AI helps IT professionals gain better insights into the causes of system anomalies and errors, allowing them to resolve issues quicker. In cyber security, AI and Machine Learning monitor systems activity and identify risks and system vulnerabilities to predict and detect threats and breaches in real-time.
E-commerce
E-commerce is a growing industry that needs automated systems to get orders quickly onto trucks for delivery. AI technologies such as robotics and machine learning can imitate human movement to perform tasks involved in manufacturing, warehousing, inventory management and fulfilment. They can pick, package and perform quality control. This creates opportunities for workers to transition to higher-skilled jobs.
E-commerce platforms have integrated AI capabilities to allow for personalised marketing content, product and service recommendations, upselling and cross-selling. Chatbots are increasingly used to provide automated responses to frequently asked questions such as those relating to product or service features, shipping options and order information.
Ways to improve your AI skills
AI tools are being adopted on a global scale. More industries need employees who have AI-expertise and soft skills such as creativity, emotional intelligence and problem-solving.
View AI as an opportunity for upskilling and career advancement. AI is always evolving so it is important that you consistently learn and adapt to new technologies.
Here are several ways to improve your AI skills:
- Study AI short courses (e.g. Coursera). You can also look at videos and tutorials online.
- Stay updated on industry trends, insights and news (e.g. AI Magazine)
- Attend AI events and workshops. You can learn from experts and network with AI professionals.
- Network or follow AI / Tech professionals on social media.
- Join online forums and community groups.
- The company you’re working at may already be using AI tools. Find out if they can be used to improve your area of work and be trained on them.
Equip yourself with AI skills in our Master of Business Analytics and Master of Information Technology courses. Learn more about studying business in Australia.
