Global Study Finds Only 22% Effectively Using Gen AI Across All Business Functions

New study from SoftServe reveals less Gen AI value than expected despite growing use cases and internal limitations SoftServe, a premier IT consulting and digital services provider, today released its findings ofthe latest studycommissioned to evaluate current Generative AI (Gen AI) use across global businesses conducted by research and advisory firm Forrester Consulting. After more than 18 months since the release of ChatGPT and growing availability of Gen AI products, solutions, and...

LONDON, 27/06/2024 (informazione.it - comunicati stampa - economia)

SoftServe , a premier IT consulting and digital services provider, today released its findings of the latest study commissioned to evaluate current Generative AI (Gen AI) use across global businesses conducted by research and advisory firm Forrester Consulting. After more than 18 months since the release of ChatGPT and growing availability of Gen AI products, solutions, and services, the study revealed businesses are still experiencing less value than executives expected with only 22% of organizations reported effectively using the technology across all business functions.

Despite falling short of expectations, Gen AI enthusiasm grows unabated according to the global survey of 777 technology purchasing decision-makers involved with their organization's use of Gen AI. Their responses indicated organizations continue to invest and pursue many use cases in search of ones that will deliver the biggest impact while simultaneously struggling with internal data readiness, governance, and skill development.

Key findings include:

“Despite a swift start to the Gen AI race, many initiatives get stuck in the piloting stages as more organizations realize their data infrastructure isn't ready to adequately deploy Gen AI technologies beyond the proof-of-concept,” “Gaps in skills and knowledge of emerging Gen AI technologies, technical feasibility, and data readiness hinder companies from moving beyond tactical wins in pilot mode to full-scale deployments enabling novel business capabilities and experiences. To make that qualitative leap to the next level, a holistic approach is required to orchestrate business priorities, use cases, and data across the technology ecosystem from the initial strategy down to the final execution.” 

While respondents agree data is paramount to effective Gen AI strategies, only 3% said their organizations' models can leverage a full range of six or more types of business data (operational, customer, employee, source code, public, and partner data), which was double the respondent average of three data types used. Moreover, a gap in technical skills persists as 88% say deeper technical expertise is becoming increasingly important for data integration, model optimization, use case development, and further application development.

Despite the over-abundance of use cases, 80% of decision-makers claim their employees are currently struggling with use case awareness and general understanding of Gen AI complexity and 90% say their organizations need a partner with more advanced technical capabilities to see transformative value in future use cases.
According to the study, companies are looking for partners with accelerated deployment support (89%) and a better understanding of their industry (88%) to help with execution and implementation.

The study revealed organizations reaping substantial value from Gen AI prioritized data, governance, and skill development with help from technical partners and experts. Of four countries surveyed, the U.S. took the lead in unlocking Gen AI value, followed by the UK, Singapore, and Germany, respectively.

Among industries, retail was most likely to harness Gen AI value and train their organization's models on owned data, while FSI (financial services and insurance) reported more likely to encounter challenges before yielding any Gen AI gains. FSI leaders also reported releasing fewer governance plans than retail and other sectors. Companies across healthcare, life sciences, oil and gas, manufacturing, ISVs, and enterprise technology depicted an even divide in achieving Gen AI value. Separately, larger businesses with revenues greater than $5 billion were less likely to show Gen AI successes due to difficulties organizing the required capabilities needed across expansive hardware, software, and infrastructure landscapes.

For more data and takeaways from the study, access SoftServe's complete study at this link .

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