Skip to main content

Generative AI will Fuel Digital Business Growth

Artificial Intelligence (AI) is a powerful tool to drive digital business growth, make better decisions, and personalize offerings to customers. As a result, forward-thinking CEOs are now actively pursuing AI investments to gain a competitive advantage.

Generative AI apps originated with tools such as ChatGPT and Stable Diffusion. According to the latest worldwide market study by ABI Research, Generative AI is forecast to add more than $450 billion to the enterprise market across twelve different vertical industries over the next seven years.

Gen AI already has hundreds of compelling use cases across these enterprise verticals. But accuracy, performance, and enterprise readiness will mean that use cases will come in three distinct waves.

Generative Artificial Intelligence Market Development

"Content-heavy verticals like marketing and education are already seeing disruption across a range of job roles in the first wave of adoption," said Reece Hayden, senior analyst at ABI Research.

Meanwhile, advertisers can now use apps more quickly, social media managers can deploy content more effectively with localization, and teachers are already developing a more personalized learning curriculum.

"The current wave of adoption will not be revolutionary. Rather, it will have an internal focus by augmenting employee productivity by providing generative tools," Hayden says.

The second wave will have a larger impact on external services. As Gen AI becomes mature with greater trustworthiness, enterprises will be able to start building products or services around it.

Service industries like healthcare and legal will increasingly leverage Gen AI to build mission-critical services. For example, healthcare enterprises can leverage these tools to manage patient health trends or build chatbots to answer healthcare questions.

Next, the third wave of enterprise adoption will be the most significant value creator.

"We expect to see verticals like manufacturing and logistics leverage Gene AI to automate and optimize processes. This will have a significant impact but also bring additional risks as hallucinations could have potentially dangerous consequences," cautions Hayden.

Although some verticals will not be widely impacted until the market matures, each vertical does have some practical use cases today. Gen AI, with human oversight, can be utilized to augment employee productivity across most business functions.

The overall outlook of Artificial Intelligence for the enterprise market is exciting, but most organizations are not in the best position as they lack a clear corporate strategy. Individual business units are merely looking at ways to deploy Gen AI to augment commercial operations.

These isolated deployments will drive fragmentation between business processes. Avoiding this requires a more careful and measured approach to enterprise deployment with a central corporate strategy on Gen AI usage, including employee usage, governance, legal approach, and expected business outcomes.

Planning now to build a framework that supports Generative AI apps deployment is critical, according to the ABI analyst assessment.

For operational consistency, enterprises should adopt a common platform that includes foundation models, low-code tools, guardrails, and curated data sets. This framework can then allow different business units to build highly contextualized, use case-specific models and applications.

Outlook for Generative AI Applications Growth

Today, Gen AI in the enterprise market is mostly nascent. Some CIOs have started building solid partnerships with IT vendors, while startup CMOs have leveraged isolated tools to augment content generation processes. But most of the market is still exploring use cases and deployment options.

For this reason, it remains to be seen how the market evolves. "But for now, given the use cases that have already been identified and the potential value on offer, Gen AI will be deployed across verticals and integrated throughout most business processes over the next seven years," Hayden concludes.

That said, I anticipate we'll see demand increase for AI Prompt Engineers who are able to fully utilize these Generative AI tools in the most effective manner, particularly in value creation applications.

Popular posts from this blog

AI Semiconductor Revenue will Reach $119.4B

The Chief Information Officer (CIO) and/or the Chief Technology Officer (CTO) will guide Generative AI initiatives within the large enterprise C-Suite. They may already have the technical expertise and experience to understand the capabilities and limitations of Gen AI. They also have the authority and budget to make the necessary investments in infrastructure and talent to support Gen AI initiatives. Enterprise AI infrastructure is proven to be expensive to build, operate and maintain. That's why public cloud service provider solutions are often used for new AI use cases. AI Semiconductor Market Development Semiconductors designed to execute Artificial Intelligence (AI) workloads will represent a $53.4 billion revenue opportunity for the global semiconductor industry in 2023, an increase of 20.9 percent from 2022, according to the latest worldwide market study by Gartner. "The developments in generative AI and the increasing use of a wide range AI-based applications in data c

Industrial Cloud Computing Apps Gain Momentum

In the manufacturing industry, cloud computing can help leaders improve their production efficiency by providing them with real-time data about their operations. This has gained the attention of the C-suite. Total forecast Industrial Cloud platform revenue in manufacturing will surpass $300 billion by 2033 with a CAGR of 22.57 percent, driven by solution providers enhancing platform interoperability while expanding partner ecosystems for application development. ABI Research found the cloud computing manufacturing market will grow over the next decade due to the adoption of new architectural frameworks that enhance data extraction and interoperability for manufacturers looking to maximize utility from their data. Industrial Cloud Computing Market Development "Historically, manufacturers have built out their infrastructure to include expensive data housing in the form of on-premises servers. The large initial upfront cost of purchasing, setting up, and maintaining these servers is

Demand for Quantum Computing as a Service

The enterprise demand for quantum computing is still in its early stages, growing slowly. As the technology becomes more usable, we may see demand evolve beyond scientific applications. The global quantum computing market is forecast to grow from $1.1 billion in 2022 to $7.6 billion in 2027, according to the latest worldwide market study by International Data Corporation (IDC). That's a five-year compound annual growth rate (CAGR) of 48.1 percent. The forecast includes base Quantum Computing as a Service, as well as enabling and adjacent Quantum Computing as a Service. However, this updated forecast is considerably lower than IDC's previous quantum computing forecast, which was published in 2021, due to lower demand globally. Quantum Computing Market Development In the interim, customer spend for quantum computing has been negatively impacted by several factors, including: slower than expected advances in quantum hardware development, which have delayed potential return on inve