Artificial Intelligence (AI) is not a wave of the future; it's the present, shaping industries and creating opportunities for businesses to extend capabilities beyond limitations. The competitive advantage that AI will bring to your business is dense with opportunity and potential. Are you ready to take advantage? How do you plan to harness its full power? Is your organization or data ready to adapt to what's been called the next "industrial revolution"? Will you be the horse (manual, analog, lagging) or the engine (innovative, efficient, perpetually driving) in the next 10 years? Let's explore how you can prepare to utilize AI to boost your business competitiveness.
Additionally, McKinsey released a study in June 2023 showing AI's impact on the Global GDP adding $2.6 trillion to $4.4 trillion. That is the equivalent to the GDP of the United Kingdom's in 2021. This technological breakthrough has the potential to change the landscape of technology and the entire business world.
Innovation Cycles are Shrinking
As important as the impact on the economy, the pace at which these innovations are arriving is changing rapidly. Innovation times have previously been benchmarked by Moore's Law, which was driven by the innovation (# of transistors on a microchip) in the semiconductor industry and used as a barometer for the technology industry's innovation at large. It states that innovation occurs every 18 months as we look to increase the throughput of our processing power. However, its ending is coincidentally timed with the presence of Artificial Intelligence and the development of quantum computing where innovation cycles are a handful of months (or less).
These are the technologies building and deepening our technology-driven economy for the next generations. They will enable innovations in robotic process automation, decision autonomy, individualized customization of consumer experiences, personalized pharmaceuticals and medical treatments, design and process streamlining, & the possibility of environmental saving breakthroughs. As you can see in the following graphic produced by Visual Capitalist using data from OpenAI's ChatGPT testing results, AI is developing at a rapidly increasing rate. Between version 3.5 and 4.0, ChatGPT improved its ability to pass the Bar Exam from the 10th Percentile to the 90th Percentile...those releases were a few months apart!
The Importance of Data
Data is the raw material that we turn into the finished good, called insights. Data is also the raw material necessary to successfully train an AI model to learn and identify the insights. Success in AI is fundamentally connected to the data you feed it. As an example, teaching yourself to speak Portuguese by using a Spanish-to-English Dictionary will not be successful. Equally, the accuracy (veracity), amount (volume), and diversity (variety) of your data foundation will result in a deeper, richer, and increasingly beneficial AI model. Without proper data, even the most sophisticated algorithms will falter from lack of care and feeding.
Data Foundation is Crucial:
Data Foundations are the basis for all decision-making in an organization. They allow for data modeling and robust data-centric decisions based on a complete scenario. As opposed to Sales/CRM-focused reports or Manufacturing/MRP-focused data, the data foundation allows both to mix and create robust Supply and Demand forecasts based on historical patterns and predicted market trends.
Structuring data in a flexible and streamlined format allows for dynamic interactions and use cases. We focus on three main functional categories: Accuracy, Consistency, and Scalability.
Accuracy: Garbage in, garbage out. If your data is flawed or incomplete, your AI models (and decisions) will produce incorrect insights.
Consistency: A strong data foundation ensures that data from various sources aligns, providing consistent and trustworthy insights.
Scalability: As your business grows, your data foundation must grow with it. Properly structured data ensures that your AI models can scale with your business.
Path to Prepared: From Current to AI-Ready
Being prepared to launch when the opportunity presents itself is a competitive advantage. Not everyone will have the foresight to embark on the preparation during the early days. Most will pause, evaluate, and continue interpreting market conditions. However, there are multiple benefits to your organization in both the short and long term. Upgrading your current data and analytics architecture will improve your organization's ability to accurately assess and adapt your business to the current conditions. Think of it as leveling the launchpad to both benefit current construction projects and the success of future launches. Here's a modernization path that can guide you in preparing for AI:
Assess the Current State:
Evaluate your existing data infrastructure
Identify gaps and areas for improvement
Hire expert assistance to confirm your environment is "launch ready"
Define Business Objectives and Key Metrics:
Outline clear goals for what you want to achieve with AI
Identify the key performance indicators (KPIs) that will measure success
Develop a Data Strategy & AI Use Cases:
Choose the types of data repositories that best fit your needs and planned usage
Data Warehouses for standard analytics and reporting
Data Lakes for mostly data science and unstructured data
Data Lakehouses for a mixture of both use cases
Reach out to Baleen Data for guidance on the appropriate architecture for you
Determine strong data governance policies, including data privacy, data classification, and data sharing with AI models
Identify Use Cases for Data & AI in your Organization
Think of AI as an "assistant" or "automation" tool
Start with a small, focused plan and expect to have multiple iterations
As an example, consider automating your AR check deposits or AP Collections Emails slowly increasing the autonomy and decision-making as your confidence in the technology builds
Build or Extend the Data Repository:
Cleanup or Create data pipelines to pull data from various sources
Maintain a complete set of immutable (unchanged and raw) transactions
Structure the data to align with your business needs and planned usage
Ensure data quality and integrity at every step
NOTE: Garbage In = Garbage Out
Invest in People, Tools, and Training:
While AI promises to take over, the people, tooling, and methods are still critical
Consider upgrading or replacing the tools to visualize and analyze data
Train your team to use these tools effectively along with AI preparation and processing
Monitor, Evaluate, and Prepare for Launch:
Continuously monitor the performance of AI and release notes/schedules
Regularly update models and strategies to align with evolving business needs
Attend conferences, consult with your experts, and seek collaboration with colleagues
Continuously improve, iterate, grow, and adapt...these next few years/decades will reward you for it!
Conclusion
Knowledge is power derived from insights. Data is the raw material we convert to insight. Therefore, data is the coal firing the "knowledge steam engine" converting data to insights to knowledge during this generation's industrial revolution.
The competitive edge that AI offers is undeniable, but the path to harnessing its full potential requires careful planning, execution, and a strong data foundation. With a strategic modernization path and the support of expert consultancies like Baleen Data, your business can embrace AI and leverage it to outpace the competition. Reach out to Baleen Data today to seize your competitive advantage.