Artificial Intelligence (AI) and cloud computing are two of the most disruptive technologies transforming businesses across industries. AI enables machines to perform tasks that require human intelligence, such as understanding natural language, recognising images, making predictions, and optimising decisions. Cloud computing provides on-demand access to scalable computing resources, such as servers, storage, databases, and infrastructure. Together, AI and cloud can create significant value for organisations by enhancing their capabilities, reducing their costs, and increasing their agility. However, to realise the full potential of AI and cloud, organisations need to adopt a strategic approach that aligns with their business goals, addresses their challenges, and leverages their strengths.
Some of the key benefits of AI and cloud are:
- Faster innovation: AI and cloud can enable organisations to develop and deploy new products and services faster and more efficiently. For example, AI can help generate creative content for marketing campaigns, such as images, videos, slogans, or logos. Cloud can provide the necessary infrastructure and tools to support the development and delivery of these content.
- Better customer experience: AI and cloud can help organizations improve their customer interactions and satisfaction. For example, AI can help analyse customer feedback, preferences, and behaviour to provide personalised recommendations, offers, or support. Cloud can enable seamless access to customer data and applications across multiple channels and devices.
- Higher productivity: AI and cloud can help automate routine tasks and processes, freeing up time and resources for more value-added activities. For example, AI can help process invoices, contracts, or claims using natural language processing and optical character recognition. Cloud can enable easy integration of these AI solutions with existing systems and workflows.
- Lower risk: AI and cloud can help organisations mitigate operational and strategic risks. For example, AI can help detect fraud, anomalies, or cyberattacks using advanced analytics and machine learning. Cloud can provide enhanced security, backup, and recovery options for data and applications.
Some of the key challenges of AI and cloud are:
Data quality: AI relies on large amounts of data to train its models and generate insights. However, data quality issues, such as incompleteness, inconsistency, or inaccuracy, can affect the performance and reliability of AI solutions. Therefore, organisations need to ensure that they have access to high-quality data that is relevant, accurate, and timely.
Talent gap: AI and cloud require specialised skills and expertise that are in high demand but short supply. Organisations need to attract and retain talent that can design, develop, implement, and manage both AI and cloud solutions. They also need to upskill their existing workforce to adapt to the changing technology landscape.
Ethics and governance: AI and cloud pose ethical and governance challenges that need to be addressed by organisations. For example, AI can raise issues of bias, fairness, transparency, accountability, privacy, or security that can affect the trust and acceptance of its users. Cloud can raise issues of compliance, sovereignty, or ownership that can affect the control and protection of data and applications. Therefore, it's important to establish clear policies and guidelines that ensure ethical and responsible use of AI and cloud.
Some of the key steps for successful AI and cloud adoption are:
Define the business problem: Organisations need to identify the specific business problem or opportunity that they want to address with AI and cloud. They need to define the scope, objectives, metrics, and stakeholders of the project. They also need to assess the feasibility, viability, and desirability of the project.
Choose the right solution: Organisations need to select the best-fit AI and cloud solution for their problem or opportunity. They need to consider the type, complexity, functionality, scalability, interoperability, and cost of the solution. They also need to evaluate the vendor’s capabilities, reputation, and support.
Implement the solution: Organisations need to plan and execute the implementation of the AI and cloud solution in a structured and agile manner. They need to follow the best practices of project management, change management, and risk management. They also need to test, monitor, and optimise the solution to ensure its quality, performance, and value.
Measure the outcome: Organisations need to measure the outcome of the AI and cloud solution against the predefined metrics and objectives. They need to collect, analyse, and report the data and feedback from the solution’s users, customers, and stakeholders. They also need to learn, improve, and scale the solution based on the results.
AI and cloud are powerful technologies that can transform businesses in various ways. However, organisations need to carefully consider their investments in AI and cloud to ensure that they get a positive return on investment. To do so, they need to implement key practices across data management, tracking results, and security, privacy, and ethics. By doing so, they can achieve a higher level of maturity and competitiveness in the digital economy.
To find out more about how KPMG can help with your cloud and AI implementation, get in touch.
