Technology is on an upward trajectory. It’s evolving at a breakneck pace and now, with the democratisation of AI, businesses need to stay ahead of the game more than ever.
This means adopting an AI-first mindset. Building an infrastructure that prioritises AI development and delivers value to customers faster than the competition.
So why is building your AI-first infrastructure like building a high-performance sports car? Let’s take a look!
The Importance of AI-First Infrastructure
Just like a sports car that’s built to go fast, an AI-first infrastructure is designed to get your business to the finish-line first.
And the numbers don’t lie. Businesses that invest in AI are more likely to outperform their peers.
A recent survey by McKinsey & Company found that companies that invest in AI and machine learning were 3x more likely to have a competitive advantage in their respective industries.
And it doesn’t end there. In fact an AI-first infrastructure can help:
- Reduce Costs: A report by McKinsey & Company found that digitization can reduce supply chain costs by up to 30%.
- Increase Efficiency: Automating repetitive tasks can free up employees’ time. Allowing them to focus on more critical tasks that require human expertise.
- Improve Visibility: Digitisation and automation provide real-time visibility into the supply chain. This allows businesses to track shipments and respond to issues quickly.
- Enhance Customer Satisfaction: A report by PwC found that 73% of customers are willing to pay more for products and services that provide superior customer experience.
Scalability and Flexibility: The Engine
Just like the engine is the heart of a high-performance sports car, scalability and flexibility are the engine of your AI-first infrastructure.
The best way to achieve this?
The cloud provides the scalability and flexibility necessary to build an AI-first infrastructure that can support your business needs.
In fact, according to a recent report by Grand View Research, the global market for cloud infrastructure services is expected to reach £1298.31 billion by 2030.
This means that your infrastructure must be built in a way that supports the ever-changing needs of AI development. Your infrastructure must be scalable to support rapid growth in data, workloads, and users.
A flexible infrastructure will allow you to quickly adapt to changes in the market, innovate faster and stay ahead of the competition.
Collaboration: Assembling the Right Team of Experts
Building a high-performance sports car requires a team of experts, building an AI-first infrastructure requires a team of professionals with diverse skill sets.
This includes the likes of data scientists, software developers, data and ML engineers, as well as IT professionals. Collaboration between different teams, departments and expertise is crucial to building an effective AI-first infrastructure.
Breaking down silos and encouraging cross-functional collaboration to promote knowledge sharing and support a culture of innovation is an essential piece of the puzzle.
However, getting the right team of experts together isn’t always easy. Or cheap.
That’s why using a consultancy to get clear direction and the manpower to build out your AI infrastructure can be highly beneficial. It gives you:
- Access to specialised expertise
- Increased efficiency
- Reduced costs
- Improved outcomes.
Prioritising Security: Building Your Car for Longevity
An important part of building a sports car to stand the test of time requires prioritising security. That’s why building an AI-first infrastructure requires security to be at the forefront of the design process.
AI models and algorithms are only as good as the data they are trained on.
Ensuring data privacy, security, and responsible use of AI are essential. In a 2017 survey by Gemalto, more than 70% of customers would abandon a company if they faced a data breach.
Thus, building an AI-first infrastructure that prioritises security is essential to maintaining trust with your customers.
How Executives Can Take The Necessary Steps
Executives who are contemplating the use of generative AI should seek to identify the areas of their business where the technology can have the most immediate effect.
This includes establishing a system to monitor it, as it will evolve rapidly.
According to Mckinsey, a great course of action is to consider fundamental issues, such as:
- Where might the technology aid or disrupt our industry and/or our business’s value chain?
- What are our policies and posture? For example, are we watchfully waiting to see how the technology evolves, investing in pilots, or looking to build a new business? Should the posture vary across areas of the business?
- Given the limitations of the models, what are our criteria for selecting use cases to target?
- How do we pursue building an effective ecosystem of partners, communities, and platforms?
- What legal and community standards should these models adhere to so we can maintain trust with our stakeholders?
Learn More About AI & Digital Disruption
Now you can see how building your AI-first infrastructure is like building a high-performance sports car.
It requires:
- A team of experts.
- The engine of scalability and flexibility.
- Prioritising security to build a car that lasts.
With an AI-first infrastructure in place, businesses can innovate faster, deliver value to customers quicker and stay ahead of the competition.
The potential of AI is limitless, and the possibilities are endless. It’s become as clear as day: Businesses that embrace AI will be the ones that thrive in the future.
So, get ready to buckle up and build your AI-first infrastructure today.
