Preparing Your Business for an AI-Driven Future

Part 2

In this part of the series I want to cover how you can practically prepare for AI driven future, and by future I mean now!

Master Your Organisation's Data: The initial and pivotal step in gearing up for AI is mastering your organisation's data. Recognised as the fuel for AI, data's quality determines the effectiveness of AI algorithms. It's essential to ensure that your data is clean, organised, and easily accessible. Continuously enhancing your data mastery is crucial for AI integration. Your data strategy should be clear and actionable, focusing on:

1. Implementing a Robust Data Governance FrameworkWhy: A data governance framework establishes the guidelines for data management and usage across the organisation, ensuring data quality, consistency, and security.How: Initiate by forming a data governance committee with members from diverse departments. Clearly define roles, responsibilities, and guidelines for data collection, storage, and usage.
2. Investing in Data Integration and StandardisationWhy: Data often exists in isolated silos across departments, hindering AI's ability to extract meaningful insights. Integrating and standardising data offers a unified perspective.How: Utilise data integration tools to amalgamate data from different sources into a consistent format, facilitating more straightforward analysis and decision-making.
3. Prioritising Data Quality and AccuracyWhy: Inaccurate data can lead to flawed AI insights, adversely affecting business decisions. Prioritising data quality is essential for AI initiatives.How: Introduce data validation checks and automate the data cleaning process. Conduct regular data audits to identify and rectify inconsistencies or errors.

Technology Architecture:

To harness the potential of AI, businesses must invest in a robust technology architecture that's scalable, secure, and agile. This encompasses cloud computing resources, data storage solutions, and high-speed networking capabilities. Every business has a unique technology landscape, shaped by various sectors and industries. Here is a modified view of layered architecture that I think needs to be in place to take advantage of the AI capabilities already available.

Use this type of model to analyse your current technology landscape and apply an AI perspective to determine future directions. This analysis will quickly reveal areas for tolerance, investment, and necessary migrations or eliminations.

The emphasis on digital transformation will shift towards a greater focus on 'AI transformation'. The rise of AI tools, especially in the business logic layer, will be evident. These tools will orchestrate applications and data to deliver user outcomes. The current traditional web/online channel's importance will diminish. Envision a world where AI assistants handle customer interactions, possibly through a 'weekly or daily briefing' during daily routines like commuting or cooking. These AI assistants will become trusted advisors and curators of content.

Delivering a Great Experience: AI can significantly elevate customer experience by automating mundane tasks, offering personalised recommendations, and predicting future customer behaviours. However, the essence of human interaction remains irreplaceable. AI should enhance, not substitute, human interactions. All business processes and value creation involve human interaction, ensuring any service delivered is exceptional. AI will understand users deeply, making the pursuit of customer data for personalisation increasingly challenging.

Consider this example: For a needs-based service like drain unblocking, traditionally, a human would initiate the process online. In an AI-driven world, AI assistants, aware of user preferences and requirements, will handle market research and only share essential user details at the right moment. Direct human interactions with websites will decrease. Moreover, real-time online reviews will influence AI assistants' recommendations, much like modern mapping apps route around traffic jams AI assistants will route their human users directly past poor service.

Businesses need to view AI assistants (Siri, Alexa, Google Assistant, etc.) similarly to how they adapted to Google and Search Engine Optimisation for E-commerce. It's no surprise these assistants require your data, especially decision support and transactional data so they can make the best most informed recommendation.

In the next part I will cover using AI to supercharge your internal processes and teams.