AI Adoption for Enterprises in 2024: Building on Initial Success

As we move through the year, AI remains a key driver of transformation and competitive advantage in the modern economy.?

The race is on—successful pilots are leading to increased investments, and organizations are now expecting not just experiments but tangible returns. They are leveraging AI to automate processes, optimize operations, and make data-driven decisions. But how many of these efforts will result in lasting success?

Join us to explore the key dynamics of AI adoption in 2024. As usual, we've curated insightful articles from N-iX experts on how AI can drive business success.

Let’s start! ??

AI Adoption: Recent Statistics and Trends ??

• By 2030, AI could boost global GDP by up to 14% due to automating processes, enhancing the workforce with AI intelligence, and increasing consumer demand for personalized AI-enhanced products. (Source: PwC)
• 65% of enterprise executives report using GenAI in at least one business function in 2024, up from one-third last year. Corporate GenAI use cases could generate $2.6 to $4.4 trillion annually. (Source: McKinsey)
• Organizations with higher gen AI expertise are adopting this technology 75% faster, gaining 59% more trust, and seeing a 78% increase in investment as they scale early benefits from their experiments. (Source: Deloitte)
• Two-thirds of companies are increasing GenAI investments, with 42% citing efficiency, productivity, and cost reduction as top benefits. (Source: Deloitte)
• 58% of executives have developed guidance for employees on AI usage. Another part says they plan to do so in another 12 months. (Source: Okta)
• In EMEA and APAC, AI is mostly used for automation and process optimization, while in the Americas, it's for Natural Language processing and understanding. (Source: Okta)
• AI could automate half of all work by 2040 - 2060, with GenAI pushing this timeline earlier. (Source: Databricks, MIT CIO Report)

In a recent study, McKinsey highlights three key technology trends within the "AI revolution" that are driving enterprise investment and adoption. Let’s explore them.

#1. Generative AI

Generative AI is becoming a dominant trend, with capabilities extending across text, code, images, audio, video, and other use cases.

Large foundation models are now integrated into enterprise software, serving various functions—from powering customer-facing chatbots to generating ad campaigns or accelerating drug discovery. The demand for efficiency and personalized experiences fuels this trend’s popularity.

With so many companies already investing in gen AI, the real question isn’t where to start but how to discover its potential quickly—and start earning the rewards.

And for those not yet scaling, it’s time to act.

Scaling GenAI for enterprise success ??

Don’t miss the keynote by N-iX Head of AI Excellence, Yaroslav Mota, as he provides strategies for scaling generative AI initiatives efficiently and successfully.

Yaroslav will share innovative approaches for navigating complexities and ensuring robust, responsible, and efficient GenAI solutions. Join us at the offline event, “Unlock the Power of Data & AI,” hosted by Amazon Web Services and N-iX, to gain the latest industry insights.

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#2. Applied AI

Applied AI technologies leverage machine learning, natural language processing, and computer vision for specific purposes. This is why companies are increasingly using data-driven insights to automate their processes, enhance capabilities, and improve decision-making.

The trend is steadily expanding across industries with many businesses seizing its potential to boost their revenue. For instance, by integrating applied AI with existing products or by creating entirely new revenue streams.

#3. Industrializing machine learning

Industrializing machine learning (ML), also known as machine learning operations (MLOps), is a set of practices that allow for scaling and maintaining ML applications within enterprises.?

These tools help transition from pilot projects to fully operational business processes and enhance team productivity. According to McKinsey research, successful ML industrializing can shorten the production timeline for ML applications by 8-10x while cutting development resources by up to 40%.

Learn more about N-iX MLOps services

Insights from N-iX Data and AI experts

Demystifying AIoT applications: invest or pass?

Artificial Intelligence is often paired with other technologies like cloud, data analytics, and recently, the Internet of Things (IoT). This combination has given rise to a new trend—AIoT. How can AI enhance IoT device performance? When does it make business and operational sense to integrate AI and IoT? What factors should you consider when deciding on AIoT applications? Read on to find out.

?? Read more

How to benefit from AI demand forecasting

Businesses often struggle to predict demand accurately due to changing market trends and consumer preferences. AI-powered forecasting and planning help organizations allocate resources efficiently, transform operations, enhance customer experiences, and drive sustainable growth. Discover AI demand forecasting use cases across 5 industries.

?? Read more

Enterprise AI governance: best practices to prevent legal and reputational damages

With AI adoption on the rise, data privacy, ethics, and regulatory compliance risks are becoming more prominent. The lack of AI governance and risk management solutions is a significant barrier to AI adoption after the cost barriers. Delve into how enterprises can implement robust AI governance with this article.

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Designing an effective AI strategy: practical guide for executives

A solid AI strategy is crucial for navigating AI adoption challenges. It outlines how businesses can use AI to achieve their goals and stay competitive. Our white paper covers the key steps: AI readiness assessment, strategy development, implementation planning, training, and ongoing support. Download it now to build a future-proof AI strategy.

AI in action ? Success stories of our clients

Streamlining operations and boosting efficiency in finance with generative AI

N-iX partnered with a fast-growing brokerage firm to develop a custom generative AI solution that significantly improved employee efficiency. The solution streamlined tasks and became a central hub for quick, accurate access to the company’s policies, services, and more.

Improving user experience of a P2P review platform with ML and NLP?

Our client, a global technology leader, offers a P2P software comparison and review platform. N-iX supported the development of a Pros and Cons feature, powered by ML and NLP, for their marketplace. Additionally, we helped create a unified solution for clustering diverse data distributions.

Enhancing ecommerce services with ML-powered churn prediction calculation

N-iX helped the client integrate ML models into their ecommerce platform to calculate churn probabilities. This upgrade allowed them to introduce features like customer segmentation, precise churn rate prediction, and personalized marketing campaigns—enhancing their overall service offerings.

Drive business value with N-iX AI expertise

Optimize operations, make impactful data-driven decisions, and reach your business goals with top AI, Machine Learning, and Data Science experts by your side. With a deep expertise across diverse sectors, we're equipped to identify and implement the most impactful use cases tailored to your business objectives.

Contact our team!

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