GENERATIVE artificial intelligence (AI) is a type of AI based technology that can create new things like stories, pictures, music, or videos based on what you ask it to do.
It works by learning from a large amount of information and using that knowledge to make something original for you.
For example, if you ask it to author a story or draw a picture, it uses what it has learned to create something new that matches your request.
This technology uses complex systems called deep learning algorithms, which mimic how the human brain works. By understanding the connections in data, generative AI can respond smartly to user requests.
This makes it helpful in many areas like chatbots, creating content, and even discovering new medicines. The main advantage of generative AI is that it can automate repetitive tasks, making work faster and more creative in many industries.
Generative AI is changing several industries by improving processes, boosting productivity, and changing how businesses operate. This article looks at how generative AI is affecting fields like finance, healthcare, manufacturing, media, and professional services.
Economic potential, industry impact
Generative AI can substantially increase economic productivity.
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According to Mackenzie, it could add between US$2,6 trillion and US$4,4 trillion each year by improving many areas such as banking and technology, for example, in banking. It could help generate an extra US$200 billion to US$340 billion every year by improving customer service and sales?
In retail the possible impact ranges from US$400 billion-US$660 billion each year. Mackenzie is an American multinational strategy and management consulting firm that offers professional services to corporations, governments and other organisations.
Transforming business functions
Generative AI is changing important business tasks by automating work and helping people do their jobs better. It is particularly useful in customer service, marketing, software development, and research and development (R&D).
For instance, in marketing, generative AI can analyse data to create detailed customer profiles and improve online content, which helps increase sales and lowers marketing costs.
Sector-specific applications
In Pharmaceuticals, Life Sciences, Media, and Manufacturing: Generative AI has the potential to revolutionise these sectors by enhancing critical processes.
In pharmaceuticals and life sciences, it can improve research and development (R&D) processes, leading to faster drug discovery and new revenue opportunities.
In media and entertainment, generative AI helps create personalised content by analysing audience preferences, which can result in innovative pricing models and disrupt traditional business practices.
Meanwhile, in manufacturing, it plays a vital role in modernising production by increasing efficiency and flexibility, allowing for more agile and responsive operations.
Together, these advancements illustrate how generative AI is transforming these industries.
Professional services
In sectors such as law, tax, accounting, and government, generative AI is significantly transforming workflow and productivity.
This technology enables professionals to quickly generate high-quality content, such as legal documents, tax reports, and analytical summaries, allowing them to focus on more strategic and complex tasks.
Legal sector: In the legal field, generative AI can help lawyers in drafting contracts, briefs, and other legal documents by analysing existing templates and case law. It not only speeds up the writing process but also helps ensure accuracy and compliance with the latest legal standards. Additionally, AI can perform document review and legal research much faster than humans, reducing the time lawyers spend on these tasks and allowing them to provide timely advice to clients.
Tax and accounting: In tax and accounting, generative AI can automate the preparation of financial reports and tax returns by organising and analysing large sets of financial data. This automation minimises human error and enhances accuracy, leading to more reliable financial statements. Furthermore, AI can be used to generate forecasts and conduct risk assessments, helping accountants and financial advisors make informed decisions for their clients.
Although the adoption of generative AI in professional services is still developing, many professionals recognise its potential benefits.
By integrating this technology, firms can improve efficiency, reduce operational costs, and allocate human resources to higher-value activities that require critical thinking and creativity.
As generative AI continues to evolve and demonstrate its capabilities, it is likely to become an integral part of the professional services landscape, driving innovation and helping organisations stay competitive in a rapidly changing environment.
Challenges
While generative AI offers numerous benefits and transformative potential across various industries, it also presents several significant challenges that organisations must carefully navigate.
These challenges include ethical questions, regulatory concerns, and the potential for bias in algorithms. Addressing these issues is crucial for companies to maximise the advantages of generative AI and to ensure responsible usage.
Ethical questions: One of the primary concerns surrounding generative AI is the ethical implications of its use. For instance, when AI creates content, questions arise about ownership and copyright. If an AI generates a piece of music or art, who owns the rights to that creation? Additionally, there are concerns about the potential for misuse of generated content, such as creating deepfakes or spreading misinformation. Companies must establish ethical guidelines to ensure that their use of AI aligns with societal values and does not lead to harmful consequences.
Regulatory compliance: As generative AI technologies continue to evolve, so does the regulatory landscape surrounding them. Governments and regulatory bodies are increasingly scrutinising AI technologies, leading to requirements for transparency and accountability. Organisations must stay informed about existing and emerging regulations that apply to AI and take steps to ensure compliance. This might involve implementing practices for data privacy protection, maintaining transparency about AI decision-making processes, and providing mechanisms for users to challenge or appeal AI-generated decisions.
Bias in algorithms: Another critical challenge is the presence of bias in AI algorithms. Since generative AI learns from data, if the training data has biases, the AI can inadvertently perpetuate or even amplify these biases in its outputs. For example, if an AI is trained on data that reflects societal inequalities; it may generate content that reinforces those prejudices, leading to unfair or discriminatory outcomes. Organisations must continuously evaluate and monitor their AI systems for bias, ensuring they use diverse and representative datasets to promote fairness and inclusivity.
Conclusion
Generative AI is a strong force for change across many industries, bringing remarkable advancements and efficiencies while transforming business tasks and creating new economic opportunities.
However, to harness its power responsibly and effectively, organisations must be proactive in addressing the challenges it poses, including ethical standards, regulatory compliance, bias mitigation, and workforce training.
By focusing on these areas, companies can ensure that the benefits of generative AI are realised across all sectors and contribute to shaping the future of work.
Additionally, it is crucial to support workers in adapting to these changes for sustainable and inclusive economic growth.
- Bangure is a filmmaker with a media degree and substantial experience in media production and management. He previously served as the chairperson of the National Employment Council for the Printing, Packaging, and Newspaper Industry. A dedicated enthusiast and scholar of artificial intelligence, Bangure combines his creative and technical skills to delve into innovative advancements. — [email protected].
