Top 3 Priorities for CXOs in Shaping Their Data and AI Strategy
The value of data is undeniable and constantly growing, and a successful Data Strategy should be the number 1 priority for CXOs invested in their company’s growth. Find the most important focus areas and how Data and AI companies can improve your game.
Data-driven decision-making has become essential in modern business in almost every sector, and customer experience is no exception. But extracting values from data is challenging, especially in a world overwhelmed by data: to give you some numbers, TechTarget reports that humanity’s collective data will reach 175 zettabytes by 2025. How much is a zettabyte? It’s ten to the twenty-first power or one trillion gigabytes.
AI services can significantly help businesses leverage the power of data, leading to smarter decision-making and enhanced customer experience. That’s why implementing a comprehensive and efficient data and AI strategy should be the number 1 priority for every CXO.
But when building a data strategy, what priorities should you focus on?
According to Databricks, there are three winning actions to be taken to design a successful strategy:
- Having access to better insights
- Strengthening data management to reduce risk
- Optimizing costs
These are the focus areas AI consulting companies generally agree upon when designing strategies for their clients, as they ensure your enterprise data and AI strategy is strong and resilient.
Insights to impact: how better insights can support growth
Organizations now have access to enormous amounts of data from different sources. CXOs have gone from focusing on traditional data, like sales, to taking semi-structured and unstructured data, like social media sentiment and customer interactions, more and more into account.
As pointed out by McKinsey, data, analytics, and technology can amplify people’s power, a feature especially important for CXOs.
The applications of data are increasing, too. From designing personalized marketing campaigns to using AI in demand forecasting, advanced analytics, and machine learning are opening up many opportunities for those ready to take them.
But data alone isn’t enough. Data relevance, reliability, and usability are all issues that prevent most companies from fully leveraging the power of their data. It is enough to think that between 60% and 73% of all data within an enterprise doesn’t get used for analytics.
Here is where AI consulting services come into play. Due to their ability to perform highly advanced data analytics, the AI consulting services market offers enterprises the possibility of finally getting the most out of their data and unleashing the true potential of data insights.
Reduce risks associated with weak data management
Unfortunately for data engineers and CXOs, data management has many risks. Cyber-attack threats are hanging on companies’ heads like the sword of Damocles, and hackers and data miners are becoming increasingly sophisticated.
The global cost of cybercrime will reach $8 trillion in 2023. To face the impact of cybercrime, organizations need to focus not only on cybersecurity but on improving cyber resilience as well.
While cybersecurity is preventive, cyber resiliency builds upon cyber security and works as an “emergency plan” for when breaches happen to minimize disruptions, protect crucial data, and recover quickly.
Ultimately, to reduce risks, CXOs need to:
- Develop a consistent way to store, process, manage, and secure data
- Adhere to the growing data privacy regulations and directives like GDPR and CCPA
- Identify all potential weaknesses and address them preventively.
Increase control over your costs with AI ML consulting
Data architectures are expensive. The price of implementing a data strategy can go from hundreds of millions of dollars for a midsize organization to billions of dollars for the largest corporations, a huge cost that few companies can afford in these turbulent times.
So, what’s the solution to decrease costs while dealing with the other two priorities on this list? A solution comes from AI ML consulting. Switching from traditional, on-premises data architectures to cloud-based ones could step up your data analysis game while reducing costs, as they can store and process more data with a less complex system. A simpler architecture will also give CXOs more control over data operations and expenses.
What do AI and ML have to do with this? AI algorithms can analyze usage patterns and suggest optimal configurations for cloud-based data structures. This allows CXOs to identify the right size of their cloud structure, avoiding unnecessary costs and using 100% of resources.
How AI Consulting Companies can Boost your Data Strategy
By 2025, the global data market is estimated to be worth $77.6 billion. Data’s relevance is becoming increasingly prominent in every business sector, with companies increasing (or planning on increasing) their investment in data-related activities.
CXOs are now faced with a double challenge: on the one hand, learning how to navigate an overwhelming amount of data, often unreliable or low quality, to extract insights. On the other hand, costs should be kept as much as possible under control.
AI services are a powerful tool in CXOs’ hands, as they support them in identifying, storing, analyzing, and securing data. Now is the time for leaders to shape the future of data and AI: the value of data is impossible to ignore and challenging to leverage.