AI proponents tout a range of benefits, including enhanced efficiency and throughput, solving complex problems, and freeing up workers to do truly creative and value-adding tasks.

The technology is already impacting our daily lives, from built-in smart assistants on smartphones such as Alexa or Siri to smart cars and drones. AI is curating our social media feeds, our music and media streaming services, and serving up online ads based on individual preferences.

If you are traveling somewhere, AI is powering Apple and Google mapping to steer us in the right direction, while it could be watching over our homes with smart home devices and monitoring our bank accounts to protect from fraud.

And with technologies like facial and object recognition continuing to improve, it will not be too long before all security camera feeds are monitored by AI, which could make clearing airport customs a lot quicker.

Future applications

Experts surveyed by Pew Research Center predict AI will amplify human effectiveness but also potentially threaten human autonomy, agency, and capabilities. Smart systems in communities, vehicles, buildings, and utilities should save “time, money and lives” and offer opportunities for individuals to enjoy a “customized” future.

However, the same experts expressed concern over the long-term impacts of these tools on the “essential elements of being human.” Key concerns included: decision-making being sacrificed; job losses; data abuse; and increased dependency, along with the risk of cybercrime.

More than 8,000 researchers, engineers, executives, and others have signed an open letter calling for “responsible AI research that recognizes social impact” and “aligns with human values.”

Buying the right hardware

Nevertheless, with AI continuing to expand, businesses need to obtain the right software and hardware to take advantage of its capabilities.

Along with graphics processing units (GPUs), a range of new hardware architecture has been developed that is optimized for machine learning, deep learning, and other AI applications.

These include neural networking processing units, field programmable gate arrays, application-specific integrated circuits, and other neurosynaptic architecture, with the development of specialized AI chips.

Others suggest AI hardware will advance from GPUs to analog devices and ultimately fault-tolerant quantum computers that can maximize system capabilities. Meanwhile, AI and machine learning tools continue to evolve for developers, too.

With AI coming in all sizes, from immense production scale to developer sandboxes and even production training, a range of hardware platforms are available for businesses.

The AI revolution may have barely begun, but smart businesses are already ramping up IT hardware and software systems to take advantage of its capabilities. After all, the Gutenberg Bible wasn’t printed overnight.