Travis TompkinsTravis Tompkins, Deloitte Consulting, LLP – Senior Manager, SAP Analytics, helps lead Deloitte's SAP Analytics Practice. He has nearly 25 years of experience with business analytics and has supported finance transformation, sales forecasting, and supply chain optimization efforts. He uses a "measures that matter" approach to drive disruptive change through analytic insights. Within the SAP space, he provides thought leadership on ECC, S4, BW on HANA, native HANA modeling, data integration, predictive / prescriptive modeling, and cognitive decision making. Currently, Travis is working with Fortune 100 Pharmaceuticals clients who are looking to innovate and optimize while still addressing pre- and post-merger restructuring of systems, organizations, and processes.

PwC is on the cusp of launching a robo-economist that could make the company the "most accurate" economic forecaster on the market. The professional services firm has developed a form of artificial intelligence (AI) with a 92% strike rate when it comes to predicting the result of UK gross domestic product (GDP). It discovered the AI's "incredible accuracy" after testing to see if the machine could pinpoint historic GDP results without knowing the outcome. But while Jonathan Gillham, PwC's director of economics, joked that the AI had already started to supersede his job, the firm said there were no plans to replace staff with automation and the program would work alongside human economists. He said: " We have been using an AI technique to forecast the UK economy and we will be launching that (...) in July. "Each quarter, the Office for National Statistics publishes its estimate for GDP and we have been able to use an AI technology base to get that right 92% of the time for the last five years.

Much of the recent AI revolution has been focused on automation through big data and/or sensors and feedback into neural networks. The resulting applications are highly valuable to businesses and consumers. They improve quality of life by optimizing labor and resources. However, these applications fall short when it comes to handling human reasoning. Much of the rationale behind the operation of these systems are implicitly embedded in the data.

Usually machine learning is discussed in terms of its impact on marketing or enterprise data, but its next frontier could be considerably more mobile, according to a research director with consulting firm Deloitte Touche Tohmatsu Ltd. In fact, in its annual technology, media, and telecommunications predictions for 2017, released this month, Deloitte's global arm has predicted that some 300 million smartphones – more than one fifth of all units sold – will incorporate machine learning, Duncan Stewart, director of technology, media, and telecommunications research for Deloitte Canada, tells ITBusiness.ca. The present numbers are being driven by smartphone chip manufacturer Qualcomm Inc.'s latest Snapdragon processors, Stewart notes, but Apple is rumoured to be developing a similar technology for their next iPhone too. "It's a boon for smartphone users," he says. "It means you get results faster, use less data, and can even complete certain tasks without being connected to a network."

AI strategy and leadership – attaining value from AI will demand recognition and action from the top of the company; therefore, the benefits must be made tangible to the C-suite and a roadmap is essential. Reinvent HR into HAIR – the Chief HR Officer's role will not only be about managing human employees, but will evolve to also manage human-machine interaction -- or Human AI Resources (HAIR). Learn with machines – to adapt their businesses to the changing nature of learning and employee training, business leaders must focus on the needs of their workforces, particularly in the area of agile skills development. Appoint a chief data supply chain officer – this position will be needed to construct an integrated, end-to-end data supply chain. Create an open AI culture – trust, openness and transparency are key for human and machine relationships to work well; business leaders must shape the corporate culture and guidelines to minimize the risks of a hybrid workforce while maximizing the opportunities.

Organizations can employ machine intelligence to automate processes, mimic human cognition, and assess information more effectively--underscoring the importance of data as the new digital currency. Machine intelligence infuses computers with capabilities simulating human cognition, allowing for more sophisticated automation and data-mining techniques that can decipher patterns, uncover insights, and guide business decision-making. And the C-suite is taking note: Spending on various aspects of machine intelligence is projected to reach nearly $31.3 billion in 2019. "We now have the ability to script and automate through bots and robotic process automation the basic tasks knowledge workers have traditionally undertaken," says Nitin Mittal, Deloitte Consulting LLP's practice leader for analytics and information management. "This is leading to dramatic improvements in enterprise efficiency and productivity."

Accenture Research shapes trends and creates data-driven insights about the most pressing issues global organizations face. Combining the power of innovative research techniques with a deep understanding of our clients' industries, our team of 250 researchers and analysts spans 23 countries and publishes hundreds of reports, articles and points of view every year. Our thought-provoking research--supported by proprietary data and partnerships with leading organizations such as MIT and Singularity--guides our innovations and allows us to transform theories and fresh ideas into real-world solutions for our clients.

Artificial intelligence can boost corporate profits by 38 percent by 2035, according to an Accenture report that gauges AI's economic impact across various industries. The report noted that AI could boost gross value added across 16 industries in 12 economies by about $14 trillion. Accenture's research team developed the report with Frontier Economics. When AI is integrated into the economy, growth rates can grow about 1.7 percent higher than the baseline. By industry, information and communication will get an AI growth rate boost of 4.8 percent by 2035, followed by manufacturing at 4.4 percent and financial services at 4.3 percent.

Accenture Report: Artificial Intelligence Has Potential to Increase Corporate Profitability in 16 Industries by an Average of 38 Percent by 2035 NEW YORK; June 21, 2017 – Businesses that successfully apply artificial intelligence (AI) could increase profitability by an average of 38 percent by 2035, according to a new report from Accenture (NYSE: ACN). The introduction of AI could lead to an economic boost of US$14 trillion in additional gross value added (GVA) across 16 industries in 12 economies. To capitalize on the opportunity, the report identifies eight key strategies for successfully implementing AI that focus on adopting a human-centric approach and taking bold and responsible steps to applying the technology within businesses and organizations. "Artificial intelligence will revolutionize how businesses compete and grow, representing an entirely new factor of production that can ignite corporate profitability," said Paul Daugherty, chief technology & innovation officer, Accenture. "To realize this significant opportunity, it's critical that businesses act now to develop strategies around AI that put people at the center, and commit to develop responsible AI systems that are aligned to moral and ethical values that will drive positive outcomes and empower people to do what they do best – imagine, create and innovate."

Stop being an "Observer" and become a "Collaborative Inventor" of the future. Companies with optimal Artificial Intelligence (AI) innovation strategies generate greater shareholder value, according to new research by Accenture. However, Accenture also found that despite these shareholder gains, only one fifth of leading companies that leverage Artificial Intelligence have achieved this performance in recent years. These companies, according to the report, have demonstrated high'AIQ' by combining strong in-house innovation and external collaboration. The research, however, only placed 17% of companies in the high performing bracket of collaboration and innovation, with a much larger 57% recognised as "Observers" and taking little action to collaborate and innovate in the AI space.