The pace of government adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies remains too slow in the face of amplified technology reliance due to the Coronavirus pandemic
The pace of government adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies remains too slow in the face of amplified technology reliance due to the Coronavirus pandemic, according to MeriTalk’s survey.
The research explores how organizations are scaling up their use of AI and ML technology to solve the public sector’s toughest challenges, and what continues to hold them back.
The survey found three quarters of government and industry executives and IT decision makers (76%) agree the COVID-19 pandemic has ratcheted up the importance of AI and ML for government. But nearly the same amount – 72% – believe that government is not doing enough to increase its pace of AI adoption.
Several factors are holding back government adoption of AI, and none of them are quick fixes. More than half of those surveyed – 56% – feel the lack of technical expertise is getting in the government’s way, while 49% cite organizational resource constraints, and 48% flag ethical/bias concerns.
The good news? In spite of these challenges, 92% of those surveyed say AI/ML technology has the potential to transform how the government solves problems.
The greatest areas of opportunity include accelerating data-driven decision making, improving forecasting and pattern recognition, and fortifying cybersecurity. Many government professionals are adjusting accordingly, with 79% either working on AI today or planning to within the next year.
Cloud and data management remain foundational to AI efforts, the MeriTalk/AWS survey found. Nearly all of those surveyed (99%) have taken steps to improve data management from edge to core to cloud. “Data matters. Data management matters. Data quality matters,” said one respondent.
In partnership with data management, 77% of attendees agree that a cloud-based infrastructure is an essential foundation for AI. If government is to keep pace with the growing need for this technology, data management and cloud integration must serve as the backbone for the process.