VP Data & AI at ECS, roles have included co-founder at a data analytics startup, VP AI at Booz Allen, and Global Analytics Lead at Accenture. As the influence of artificial intelligence grows, it is increasingly vital to design processes and systems to harness AI while counterbalancing risk. Our charge is to eliminate bias, codify objectives and represent values. Responsible AI ensures alignment to our standards spanning data, algorithms, operations, technology and Human Computer Interaction. I am examining the importance of each of these elements in a series of articles.

Omnia's Trustworthy AI Module, Deloitte's unique artificial intelligence evaluation technology, has been recognized as'Digital Innovation of the Year' at the Digital Accountancy Forum and Awards 2021 in London earlier this week. This marks the second consecutive year Deloitte has garnered top honors for delivering innovative and disruptive technologies by The Accountant and International Accounting Bulletin. It also marks the fourth time Deloitte has won the award overall. Omnia DNAV, a digital cloud-based solution that revolutionizes the audit of securities and investments, was honored with the award in 2020. Deloitte won the 2018 'Audit Innovation of the Year' for its audit-transforming Cortex data platform and in 2015 for functionality using artificial intelligence that quickly identifies, extracts, and analyzes information across an entire population of documents.

More enterprises have adopted RPA functions to automate rote, repetitive tasks, but sometimes they need more capabilities. Enter machine learning functions and the result is "intelligent automation" which, unlike RPA, can learn and adapt. The choice between the two should depend on the use case, but in today's AI-crazed world, there's a misconception that intelligent automation must be better when, in fact, robotic process automation (RPA) may be a more elegant solution. "We view AI/ML as knowing what to do, RPA is knowing how to do it," said Muthu Alagappan, chief medical officer at intelligent automation platform provider Notable Health. "For example, OCR can be used to extract information from insurance cards, photo IDs and clinical documents. From there, RPA [enters] the extracted data into existing systems of record." RPA simply executes its programming, so if requirements change, it needs to be reprogrammed.

Derek Snaidauf is a Principal with Deloitte Transactions and Business Analytics LLP. He is a recognized expert in Artificial Intelligence, Trustworthy AI, Cyber, and Cloud, and is a frequent author and speaker on these topics. Derek holds leadership roles in Deloitte's Strategic Growth Offerings, Analytics & Technology, and Regulatory & Legal Support practices. During his 20 year management consulting and professional services career, Derek has helped numerous clients across industries navigate complexity, boost performance, and anticipate change. He supports them end-to-end on strategy, organizational design, process transformation, data science, and technology.

The real big leap in automation comes with the combination of RPA and smart voice and chatbots. Deloitte is at the forefront of this and uses Cognigy.AI not only with its customers but also internally in the HR department. Peter Fach showed an example of how a department head can pay a bonus to selected employees. Previously, this required contact with an HR employee, who provided information on the bonus program, answered queries and then took over the handling (booking, payment, etc.). Now, the team lead is guided through the process in the HR portal by a Cognigy AI-based chatbot.

AI adoption and maturity levels are significantly lower at other types of technology companies, with many companies insisting on seeing sector-specific use cases and proven results before scaling up their AI programs and investments. Many existing AI efforts in the sector are limited to scattered experiments and small-scale pilots, without an overarching strategy for harnessing the full power of AI and digital data. As more organizations shift their AI workloads to a cloud environment, data integration challenges are intensifying. Some of the most common barriers to access third-party data sources include dealing with disparate data that exists on different systems and merging data from diverse sources. For all these efforts, the right talent and expertise can be critical.

Skepticism about how productive employees could be if they worked from home also eroded. An April 2021 study from the Becker Friedman Institute at the University of Chicago examined companies' post-covid remote work plans and found a predicted productivity boost of 5% for the US economy. And a December 2020 survey by PwC found that 34% of employees said they were more productive than before the pandemic, while over half of executives said average employee productivity had improved. Now, an equally widespread disruption is underway in the form of hybrid work: while some organizations are insisting workers return to the office full-time, many are prepping for a new normal where employees spend some days in the office and some days working remotely, with a combination of virtual and in-person meetings and collaboration. A CNBC survey of executives in human resources, finance, and technology found that just under half of companies will use a hybrid work model in the second half of 2021.

Employees with the right skills make or break an enterprise, create brand impression, represent the company's culture and values. Disruptive technology is changing the contemporary work environment. Employees in traditional roles are now feeling insecure and disengaged. This dissonance threatens to take away the Competitive Advantage of companies. Employee Engagement has emerged as one of the significant pillars on which the Competitive Advantage, Productivity, and Growth of an organization rests.

Deloitte today released the fourth edition of its State of AI in the Enterprise report, which surveyed 2,857 business decision-makers between March and May 2021 about their perception of AI technologies. Few organizations claim to be completely AI-powered, the responses show, but a significant percentage are beginning to adopt practices that could get them there. In the survey, Deloitte explored the transformations happening inside firms applying AI and machine learning to drive value. During the pandemic, digitization efforts prompted many companies to adopt AI-powered solutions to back-office and customer-facing challenges. A PricewaterhouseCoopers whitepaper found that 52% percent of companies have accelerated their AI adoption plans, with global spending on AI systems set to jump from $85.3 billion in 2021 to over $204 billion in 2025, according to IDC.

Amazon Web Services are looking for a passionate and talented Applied Scientist who will collaborate with other scientists and engineers to develop computer vision and machine learning methods and algorithms to address real-world customer use-cases. You'll design and run experiments, research and develop new algorithms, and put your algorithms and models into practice to help solve our customers' most challenging problems. This role resides in AWS Professional Services, a unique consulting team where we pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you do not live in a market where we have an open Applied Scientist position, please feel free to apply. Our Applied Scientists can live in any location (D.C, Maryland, Virginia, Illinois, Pennsylvania, New York, New Jersey, Denver) where we have a WWPS Professional Service office.