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How you can use AI right now to shape your company’s future

If you're feeling FOMO surrounding AI, fear missing out no longer. Ollion is here to share how you (yes, you!) can use AI to shape the future of your organization.

2024-02-20

AI technologies – such as GPT, LaMDA and BLOOM – can be daunting to wrap your head around, especially in applications specific to your industry or your role within your organization. AI is driving digital transformation that presents opportunities unlike anything we’ve previously experienced. As a result, there’s a fear of missing out if you’re not implementing this new technology into your workflows and teams to keep up with the competition.

“It’s time to catch up! How can we use AI right now,” you may be thinking. However, rushing to use AI without a strategy could do more harm than good. Rather than succumbing to the FOMO and mindlessly engaging with AI, you can start by reading the rest of this article. (Yes, the answer to this piece’s title is “You can’t.”) We’ll look at how to utilize AI systems within your organization, the necessary processes for building a solid foundation around AI and how to continuously grow your AI capabilities as the technology evolves.

All machine learning is artificial intelligence, but not all artificial intelligence is machine learning.

Artificial intelligence (AI) and machine learning (ML) are part of the daily vernacular as of late, but often (and inaccurately), they are used interchangeably. Let’s clearly define the difference and relationship before we discuss strategy for your organization.

ML processes vast amounts of data and identifies patterns and relationships to help AI algorithms make increasingly accurate predictions and decisions without explicit programming. Typically, ML is more difficult and expensive to operate and design, and it shouldn’t be implemented until a solid AI foundation has been established in a narrower use case. ML’s primary use case is the enablement of learning and processing complex amounts of data to help improve the functionality of the AI it’s working within. Trying to implement ML without a strong AI base is akin to attempting to build a skyscraper out of toothpicks – it’s going to collapse and ultimately cost you more than it produces.

How to utilize AI in your business (for real this time)

Many organizations are prone to jumping the gun when applying AI to their processes and data strategy, so it’s important to remember that starting small and slow will turn out more long-term benefits. To begin, identify the low-hanging fruit: explore specific tasks or processes within your organization that could be easily automated or optimized using AI. This generally applies to repetitive tasks, data analysis or decision-making processes that would otherwise consume significant amounts of time and resources. It’s also wise to experiment with AI tools and platforms to see which could be easily integrated into existing workflows, such as natural language processing, image recognition and predictive analytics.

Even though AI is powerful and can increase your organization’s efficiency, AI is not a “fix-all” solution. We tout the benefits of AI, but these benefits don’t apply to every situation and using AI may not always be the best approach. For example, businesses that have well-defined business rules and processes may find AI is not cost-effective or doesn’t add enough value to warrant the investment in talent, infrastructure and ongoing maintenance that are often required. If your business operates with clearly defined rules and regulations, AI may struggle to comply and may not consider the context and nuances that are taken into account by human decision-makers to comply with these rules. So, while AI can be a valuable tool, organizations must carefully assess the benefits and costs of implementations as it relates to their specific objectives.

As you gain a clearer understanding of where AI technology can be utilized most effectively within your organization, you open up opportunities to significantly reduce the time and effort required to perform tasks, both physically and digitally. AI’s ability to operate around the clock offers an undeniable benefit for business processes that require continuous monitoring and action. Examples include AI systems monitoring website performance, analyzing customer experience or managing cybersecurity threats even when staff is unavailable.

Moreover, AI learns from data and makes adaptive decisions allowing it to continuously improve algorithms and optimize processes based on real-time insights and responses under variable conditions. This enables more accurate, personalized, intelligent automation processes for enhanced decision-making. With that, businesses can overcome bottlenecks in operations and limited human resources by improving the efficiency of processes and augmenting human capabilities.

When implemented thoughtfully, AI can impact the bottom line of your business by increasing scalability, agility and productivity to make your organization more competitive in today’s rapidly changing business landscape.

Do the AI two-step.

A strong foundation around AI involves both the data and the people within your organization. These are the essential first steps in building a robust AI foundation:

1. Prepare your data.

Clean, high-quality data is crucial for AI to generate accurate and reliable insights. Data labeling is a key factor in training AI models and should be prioritized early. Investment in data management and data governance practices will help maintain the cleanliness and integrity of your data. This includes ensuring data security, privacy compliance and data accessibility.

The next phase is to create a robust data management framework that unifies both traditional analytics and AI. A data management framework will ensure consistency that enables seamless data integration, which is vital for applications requiring access to multiple data sources. It’s also essential to comply with existing and future data standards and to build infrastructure that safeguards sensitive information while ensuring AI algorithms can access what they need to deliver valuable insights. When you outline well-defined processes for existing reporting and analytics, you can establish a baseline and determine in which areas AI can provide the most value.

As you advance into your AI journey, carry a forward-thinking approach and create centralized data platforms that cater to analytics, applications and AI initiatives, which will help avoid duplication of data pipelines and reduce operational overhead as you move into a more AI-powered model.

2. Prepare your people.

The human element is just as essential as data in AI implementation. Most importantly, the entire organization should embrace a culture of empowered experimentation and exploration. When teams are utilizing newer and riskier technologies like AI, the appropriate company culture will support the inevitable process of trying and failing.

Within your company, you most likely already have the right individuals to spearhead your AI projects. Some of the best people to lead the new generation of AI are not the most technical and usually work closer to business problems than technical ones. Curiosity and problem-solving abilities are valuable traits, especially as you encourage experimentation with AI tools and frameworks within your organization. Open-mindedness can trump pure raw technical abilities or a background in data science, ML or AI. If your organization lacks in-house AI expertise, it could be beneficial to consider collaboration with external experts to accelerate your AI journey and provide insights into best practices and industry trends.

Ready to grow with AI?

Continued experimentation with AI tools and frameworks will help you stay ahead of the curve. You can position your business to maximize its potential by harnessing the power of AI. A great way to start is by connecting with AI professionals to discuss questions regarding your organization’s readiness to adopt AI and how to guide your organization through the ever-changing landscape that AI presents.

Ollion’s AI consulting services design end-to-end data and AI strategies and leverage modern technologies to create data-driven business solutions to achieve your goals. Our team is here to help you navigate the shifting and complex landscape, so your enterprise can make the most of the digital technology at your disposal and enable a successful AI-driven digital transformation. Discover the potential of AI to improve your organization and position yourself as a leader in your industry by reading The business leader’s guide to AI or contacting Ollion about our AI solutions today.